{"query_echo":{"q":"","filters":{"geography":["Freedonia"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'Freedonia' for facet 'geography' is not in the controlled vocabulary."}]},"total":{"value":2,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?geography=Freedonia","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-001451","url":"https://climateinsightsdirectory.org/document/sei-001451","title":"Low Emissions Analysis Platform Training Exercises","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":"2020-09-17","source_url":"https://leap.sei.org/documents/LEAPTrainingExerciseEnglish2020.pdf#page=69&zoom=100,102,86","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The guide outlines seven exercises for the LEAP 2020 software. It covers basic energy demand and supply modeling, the creation of baseline and policy scenarios, cost-benefit analysis, the inclusion of non-energy greenhouse gas emissions, transportation-specific analysis, and least-cost electricity generation optimization. The exercises use a fictional case study, Freedonia, to demonstrate how to enter data, use functions like interpolation and growth rates, and analyze results through tables and charts.","ai_generated":true,"unit":"sei-001451#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The training uses a fictional country, Freedonia, to simulate real-world energy data, featuring a mix of industrialized urban areas with OECD standards and rural areas reliant on biomass fuels.","ai_generated":true,"unit":"sei-001451#insight-1","date_modified":"2026-10-23"},{"text":"LEAP allows for the creation of 'Baseline' scenarios to project energy requirements in the absence of new policy measures, and 'Policy' scenarios to evaluate the impact of efficiency measures or technology switches.","ai_generated":true,"unit":"sei-001451#insight-2","date_modified":"2026-10-23"},{"text":"The software supports 'Transformation' modules to model energy conversion processes, such as electricity generation, oil refining, and charcoal production, allowing users to specify plant capacities, efficiencies, and dispatch rules.","ai_generated":true,"unit":"sei-001451#insight-3","date_modified":"2026-10-23"},{"text":"LEAP can perform integrated cost-benefit analysis from a societal perspective, incorporating demand costs, transformation capital and O&M costs, fuel costs, and environmental externality costs.","ai_generated":true,"unit":"sei-001451#insight-4","date_modified":"2026-10-23"},{"text":"The platform can incorporate non-energy sector greenhouse gas emissions, such as methane and nitrous oxide from agriculture (manure management) and HFCs from refrigeration, following IPCC inventory guidelines.","ai_generated":true,"unit":"sei-001451#insight-5","date_modified":"2026-10-23"},{"text":"LEAP includes specialized transportation analysis features that use the 'Stock Turnover Method' to model vehicle sales, stocks, mileage, and fuel economy for different vehicle types like cars and SUVs.","ai_generated":true,"unit":"sei-001451#insight-6","date_modified":"2026-10-23"},{"text":"The software features optimization capabilities (via the OSeMOSYS model) to identify the least-cost combination of power plants to meet demand, which can be further constrained by CO2 emission caps.","ai_generated":true,"unit":"sei-001451#insight-7","date_modified":"2026-10-23"}],"climate_tags":["greenhouse gas emissions","electricity generation","biogas"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["technical guide","training manual"]},{"id":"sei-000838","url":"https://climateinsightsdirectory.org/document/sei-000838","title":"Visibility of Land-Based Resource Variables","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.leap.sei.org/help24/Land-based_Resource_Calculations/Visibility_of_Land-Based_Resource_Variables.htm","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document provides a step-by-step procedure for activating land-based resource calculations in LEAP, starting with enabling the 'Land-Use Change and Land-Based Resources' option in the Scope & Scale settings. It details the necessity of defining land types and regions, as well as configuring resource properties in the General: Fuels screen. The guide notes that enabling these settings reveals new branches in the main tree for specifying land areas and conversions, and that the available variables under the Resources branch vary depending on whether the user is analyzing wood resources or other renewable energy forms like solar, wind, and biomass.","ai_generated":true,"unit":"sei-000838#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"To activate land-based resource analysis in LEAP, users must first enable the 'Land-Use Change and Land-Based Resources' option in the Scope & Scale tab of the General: Settings screen; otherwise, all related variables are hidden and excluded from calculations.","ai_generated":true,"unit":"sei-000838#insight-1","date_modified":"2026-10-23"},{"text":"Setting up a land-based resource analysis requires creating a list of land types and, because these analyses typically require geographic disaggregation, the authors recommend using a multi-regional model for sizable energy systems such as countries.","ai_generated":true,"unit":"sei-000838#insight-2","date_modified":"2026-10-23"},{"text":"The software provides different levels of detail based on the resource type: wood resources include complex variables for stocks, growth, and demand/supply interactions, whereas other resources (such as solar, wind, and biomass) only consider annual energy productivity.","ai_generated":true,"unit":"sei-000838#insight-3","date_modified":"2026-10-23"}],"climate_tags":["land-use change","biomass","solar energy","wind power","renewable energy","energy modeling"],"geography_discussed":["Freedonia"],"frame_perspective":[],"analysis_type":["technical guide"]}]}