{"query_echo":{"q":"","filters":{"analysis_type":["User Guide"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'User Guide' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":6,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=User+Guide","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":"eninnova-000121","url":"https://climateinsightsdirectory.org/document/eninnova-000121","title":"INDUSTRIAL TRANSFORMATION TECHNOLOGY AND INVESTMENT MODEL DOCUMENTATION","publisher":{"name":"Energy Innovation","organization":"energy-innovation"},"document_type":"guide","language":"en","date_published":"2026-04","source_url":"https://energyinnovation.org/wp-content/uploads/ITTIM-Documentation-v1.1.0.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The Industrial Transformation Technology and Investment Model (ITTIM) is an Excel-based tool that estimates energy use, CO2 emissions, and capital investment needs for industrial decarbonization. It employs a six-tier cumulative technology framework—ranging from energy efficiency to clean chemical feedstocks—to mitigate 97% to 99% of industrial emissions. The model currently supports datasets for China, India, Indonesia, Viet Nam, the Philippines, and the United States, allowing users to simulate various scenarios including carbon pricing and different hydrogen cost projections.","ai_generated":true,"unit":"eninnova-000121#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The ITTIM utilizes a cumulative six-tier technology framework to address industrial emissions, which together can mitigate between 97% and 99% of energy-related and cement calcination emissions in each modeled region.","ai_generated":true,"unit":"eninnova-000121#insight-1","date_modified":"2026-10-23"},{"text":"The technology tiers are prioritized by cost, maturity, and practicality: Tier 1 focuses on material and energy efficiency; Tier 2a and 2b cover electrification of low- to high-temperature processes; Tier 3 implements Carbon Capture and Use or Storage (CCUS); Tier 4a replaces remaining fossil fuels with green hydrogen; and Tier 4b transitions to clean chemical feedstocks.","ai_generated":true,"unit":"eninnova-000121#insight-2","date_modified":"2026-10-23"},{"text":"The model's geographic scope includes datasets for China, India, Indonesia, Viet Nam, the Philippines, and the United States (including 48 contiguous states), which collectively represented 64% of global industrial energy-related CO2 emissions in 2019.","ai_generated":true,"unit":"eninnova-000121#insight-3","date_modified":"2026-10-23"},{"text":"The ITTIM estimates both energy costs and capital equipment costs, though it excludes costs for land, buildings, installation, and operations and maintenance.","ai_generated":true,"unit":"eninnova-000121#insight-4","date_modified":"2026-10-23"},{"text":"The model allows users to simulate carbon pricing from $0 to $250 per tonne of CO2, which affects the cost-effectiveness of interventions but does not change the choice of technologies because the tool is not a cost-driven optimization model.","ai_generated":true,"unit":"eninnova-000121#insight-5","date_modified":"2026-10-23"},{"text":"Green hydrogen costs in the 'High Improvement' scenario for 2050 vary by region, ranging from $1.80/kg in China and India to $3.53/kg in the Philippines.","ai_generated":true,"unit":"eninnova-000121#insight-6","date_modified":"2026-10-23"}],"climate_tags":["Industrial decarbonization","energy efficiency","electrification","green hydrogen","blue hydrogen","carbon price"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical documentation","user guide","modeling framework"]},{"id":"eninnova-000096","url":"https://climateinsightsdirectory.org/document/eninnova-000096","title":"GETTING STARTED WITH EPS","publisher":{"name":"Energy Innovation","organization":"energy-innovation"},"document_type":"guide","language":"en","date_published":"2025-07-30","source_url":"https://energyinnovation.org/wp-content/uploads/Getting-Started-with-EPS.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document is a quick start guide for the Energy Policy Simulator (EPS), a tool developed by Energy Innovation to help users model state-level energy systems and climate policies. Using Louisiana as an example, it explains how to access the simulator, apply specific policies such as a Clean Electricity Standard or Building Component Electrification, and analyze results through CO2e emission graphs and wedge diagrams. It also describes how to use pre-designed scenarios, including the NDC Scenario and the Federal Policy Repeal and Rollback scenario, to test different decarbonization pathways.","ai_generated":true,"unit":"eninnova-000096#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The Energy Policy Simulator (EPS) allows users to model state energy systems by applying various policies to determine the most cost-effective and beneficial combinations for reducing carbon emissions, utilizing 1.7 million equations for each year of calculation.","ai_generated":true,"unit":"eninnova-000096#insight-1","date_modified":"2026-10-23"},{"text":"The simulator provides a range of output metrics beyond total CO2e emissions, including health impacts, financial data, and sector-specific results for industry, transportation, buildings, and electricity.","ai_generated":true,"unit":"eninnova-000096#insight-2","date_modified":"2026-10-23"},{"text":"Users can customize the implementation schedules of policies to account for the slow turnover of equipment; for example, accelerating building heating electrification to 2035 can shift emissions more effectively than a 2050 target.","ai_generated":true,"unit":"eninnova-000096#insight-3","date_modified":"2026-10-23"},{"text":"The tool includes pre-configured scenarios for comparison, such as the NDC Scenario for ambitious decarbonization and a Federal Policy Repeal and Rollback scenario that aligns with the \"One Big Beautiful Bill Act\" and proposed EPA rule repeals.","ai_generated":true,"unit":"eninnova-000096#insight-4","date_modified":"2026-10-23"}],"climate_tags":["carbon dioxide emissions","energy policy","sustainable energy","decarbonization"],"geography_discussed":["Louisiana"],"frame_perspective":[],"analysis_type":["user guide","technical walkthrough"]},{"id":"iisd-002331","url":"https://climateinsightsdirectory.org/document/iisd-002331","title":"WEFsat-Mining Tool User Guidance Manual","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"guide","language":"en","date_published":"2015-09","source_url":"https://www.iisd.org/system/files/publications/WEFsat-mining-tool-user-guidance-manual.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The WEFsat-Mining Tool User Guidance Manual describes a methodology for assessing how mining affects the water-energy-food nexus. It guides users through a four-step process: establishing a community WEF baseline, identifying mining-specific influences, determining mitigation and enhancement actions, and summarizing findings for decision-makers. The tool utilizes a framework focusing on availability, access, supporting infrastructure, and supporting policies.","ai_generated":true,"unit":"iisd-002331#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The WEFsat-Mining tool is based on a framework that analyzes four primary components affecting a community's security: access, availability, supporting resources, and supporting policies across water, energy, and food supplies.","ai_generated":true,"unit":"iisd-002331#insight-1","date_modified":"2026-10-23"},{"text":"The assessment process is structured into four sequential steps: (1) understanding current community WEF status and linkages, (2) identifying potential mining benefits and impacts, (3) exploring actions and indicators, and (4) summarizing results for decision-makers.","ai_generated":true,"unit":"iisd-002331#insight-2","date_modified":"2026-10-23"},{"text":"The tool requires a deliberative, iterative process involving stakeholders, typically conducted through one-on-one meetings, virtual correspondence, and workshops led by a trained facilitator.","ai_generated":true,"unit":"iisd-002331#insight-3","date_modified":"2026-10-23"},{"text":"The tool emphasizes a temporal perspective by requiring users to describe mining characteristics and impacts at two distinct stages: full operations and full closure.","ai_generated":true,"unit":"iisd-002331#insight-4","date_modified":"2026-10-23"},{"text":"Users can track WEF security and mining impacts using three types of indicators: status indicators, pressure indicators, and action indicators, with a suggested database embedded in the tool.","ai_generated":true,"unit":"iisd-002331#insight-5","date_modified":"2026-10-23"},{"text":"The complete analysis process, including preparation, stakeholder consultation, and data analysis, is estimated to take between two to six weeks.","ai_generated":true,"unit":"iisd-002331#insight-6","date_modified":"2026-10-23"}],"climate_tags":["water security","energy security","food security","mining","sustainable development","climate change adaptation","environmental impact assessment","ecosystem service"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["user guide","methodological framework"]},{"id":"sei-001389","url":"https://climateinsightsdirectory.org/document/sei-001389","title":"GREAT 能源分析工具","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"zh","date_published":"2012-07","source_url":"https://cdn.leap.sei.org/documents/GREAT_Tool_Manual.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document is a user guide for the Green Resources and Energy Analysis Tool (GREAT), an application framework based on the Long-range Energy Alternatives Planning (LEAP) software. Developed by the China Energy Program at Lawrence Berkeley National Laboratory, GREAT is specifically designed for energy policy analysis and emission assessments at the provincial and municipal levels in China.","ai_generated":true,"unit":"sei-001389#summary","date_modified":"2026-08-17"},"key_insights":[{"text":"GREAT is a specialized application framework built upon the LEAP software, which was developed by Charlie Heaps at the Stockholm Environment Institute (SEI) US center and is used in over 150 countries for energy policy analysis and climate change mitigation assessment.","ai_generated":true,"unit":"sei-001389#insight-1","date_modified":"2026-08-17"},{"text":"The GREAT tool is structured into four primary branches: Main Assumptions, Demand, Transformation, and Resources. It allows for separate modeling of urban and agricultural areas to account for their differing energy consumption characteristics.","ai_generated":true,"unit":"sei-001389#insight-2","date_modified":"2026-08-17"},{"text":"Energy demand modeling in GREAT is based on an accounting model where energy consumption is calculated as the product of activity level and energy intensity.","ai_generated":true,"unit":"sei-001389#insight-3","date_modified":"2026-08-17"},{"text":"The tool supports emission analysis for greenhouse gases and other pollutants, such as carbon dioxide, methane, and sulfur dioxide. It can utilize default IPCC Tier 1 emission factors or local actual data for these calculations.","ai_generated":true,"unit":"sei-001389#insight-4","date_modified":"2026-08-17"},{"text":"GREAT utilizes a scenario management system that allows users to create new scenarios by inheriting structures and data from a parent scenario (such as a reference scenario), simplifying the process of analyzing different policy or technical assumptions.","ai_generated":true,"unit":"sei-001389#insight-5","date_modified":"2026-08-17"}],"climate_tags":["energy transition","greenhouse gas emissions","energy policy","climate change mitigation"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["User Guide","Technical Manual"]},{"id":"sei-001450","url":"https://climateinsightsdirectory.org/document/sei-001450","title":"LEAP Long-range Energy Alternatives Planning System Volume 2","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":"1992-03","source_url":"https://leap.sei.org/documents/LEAPManual_1992.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The LEAP system is a computer-based simulation tool for energy policy analysis. It uses a modular structure consisting of Energy Scenario programs (Demand, Transformation, Biomass, Environment, and Evaluation), an Aggregation program for multi-spatial planning, and an Environmental Data Base (EDB) for emission coefficients. The system allows users to create a 'base case' and develop alternative policy scenarios to assess physical, economic, and environmental impacts.","ai_generated":true,"unit":"sei-001450#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"LEAP is designed as a \"computer-based accounting and simulation tool\" to help policy makers evaluate energy policies and develop \"sustainable energy plans\" by projecting supply and demand patterns.","ai_generated":true,"unit":"sei-001450#insight-1","date_modified":"2026-10-23"},{"text":"The system utilizes scenario analysis, starting with a \"business-as-usual\" scenario known as the \"base case,\" which users can then modify to create alternative policy scenarios to answer \"what if\" questions.","ai_generated":true,"unit":"sei-001450#insight-2","date_modified":"2026-10-23"},{"text":"The Demand program employs a hierarchical four-level data structure consisting of Sector, Subsector, End Use, and Device to calculate energy requirements.","ai_generated":true,"unit":"sei-001450#insight-3","date_modified":"2026-10-23"},{"text":"Demand projections can be calculated using three methods: Interpolation, Growth Rate, or by linking to Macro-Drivers (with optional elasticities).","ai_generated":true,"unit":"sei-001450#insight-4","date_modified":"2026-10-23"},{"text":"The Transformation program simulates the conversion of primary energy resources to final fuels through modules, which can be categorized as Simple, Transmission and Distribution, Detailed, or Electricity Type.","ai_generated":true,"unit":"sei-001450#insight-5","date_modified":"2026-10-23"},{"text":"Electricity modules in the Transformation program can simulate plant dispatching by \"merit order\" to meet both annual energy requirements and instantaneous peak loads using either a default or user-defined load curve.","ai_generated":true,"unit":"sei-001450#insight-6","date_modified":"2026-10-23"},{"text":"The Biomass program provides a physical inventory of biomass sources based on a three-tier land structure: Subareas, Zones, and Landtypes.","ai_generated":true,"unit":"sei-001450#insight-7","date_modified":"2026-10-23"},{"text":"The Environment program estimates emissions by linking Demand and Transformation data to the Environmental Data Base (EDB), which contains coefficients for air, water, and land emissions and health and safety impacts.","ai_generated":true,"unit":"sei-001450#insight-8","date_modified":"2026-10-23"},{"text":"The Evaluation program performs a social cost-benefit analysis by comparing a 'Reference case' and an 'Alternative case,' focusing on social costs rather than project financial viability.","ai_generated":true,"unit":"sei-001450#insight-9","date_modified":"2026-10-23"},{"text":"The Aggregation program enables coordinated planning across multiple spatial levels, allowing data to be aggregated from the county or district level up to the \"multinational or global level.\"","ai_generated":true,"unit":"sei-001450#insight-10","date_modified":"2026-10-23"},{"text":"The Environmental Data Base (EDB) is structured as a matrix where rows are 'Source categories' (technologies/processes) and columns are 'Effects categories' (emissions/impacts).","ai_generated":true,"unit":"sei-001450#insight-11","date_modified":"2026-10-23"}],"climate_tags":["environmental emission","electricity generation","land-use planning","greenhouse gas emissions","energy efficiency"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["user guide","technical manual"]},{"id":"wri-001085","url":"https://climateinsightsdirectory.org/document/wri-001085","title":"Getting Started with Aqueduct","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://www.wri.org/aqueduct/help-center/how-use-analysis-features-water-risk-atlas","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The Aqueduct Water Risk Atlas is an interactive tool for analyzing global water risk. Users can specify locations via map selection, address entry, or file imports of up to 500 addresses. The tool provides various water risk indicators—including physical, regulatory, and reputational risks—with temporal resolutions (annual and monthly) and future projections for 2030, 2050, and 2080 based on CMIP6 climate data and five Global Circulation Models. Results can be exported in CSV and GPKG formats.","ai_generated":true,"unit":"wri-001085#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Users can define geographic areas for water risk analysis through three primary methods: clicking points on an interactive map, entering specific addresses or coordinates (decimal degrees or Degrees-Minutes-Seconds), or importing files containing up to 500 addresses.","ai_generated":true,"unit":"wri-001085#insight-1","date_modified":"2026-10-23"},{"text":"The tool offers a variety of water risk indicators categorized by type, including overall water risk, physical risks (quantity and quality), and regulatory and reputational risk.","ai_generated":true,"unit":"wri-001085#insight-2","date_modified":"2026-10-23"},{"text":"Aqueduct provides future water risk projections for the years 2030, 2050, and 2080, utilizing the latest CMIP6 climate data and the median of five Global Circulation Models across pessimistic, business as usual, and optimistic scenarios.","ai_generated":true,"unit":"wri-001085#insight-3","date_modified":"2026-10-23"},{"text":"Analysis results can be exported in CSV and GPKG formats, with the volume of data varying by selection: annual exports provide 271 columns, monthly exports provide 28 columns, and future exports provide 123 columns.","ai_generated":true,"unit":"wri-001085#insight-4","date_modified":"2026-10-23"}],"climate_tags":["water scarcity","climate data"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["user guide"]}]}