{"query_echo":{"q":"","filters":{"analysis_type":["pilot study"]},"warnings":[]},"total":{"value":45,"relation":"eq"},"page":3,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=pilot+study&page=3","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":"transfor-000041","url":"https://climateinsightsdirectory.org/document/transfor-000041","title":"Metodologías complementarias para el seguimiento de comunidades energéticas en Colombia","publisher":{"name":"Transforma","organization":"transforma"},"document_type":"report","language":"es","date_published":null,"source_url":"https://transforma.global/wp-content/uploads/2026/06/260610-Metodologias-complementarias-C.E-V2.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report describes two distinct but complementary tools for monitoring energy communities in Colombia: a national-scale longitudinal tracking tool by Transforma and a deep socioeconomic evaluation tool by ICSI. While Transforma's methodology focuses on the project life cycle (planning, construction, and operation) via community representatives, ICSI's approach uses household-level surveys to analyze territorial transformations. The document argues that using these tools in sequence or simultaneously provides a more robust diagnosis by combining organizational perspectives with real-world territorial conditions, as demonstrated by a pilot application in Tomarrazón, La Guajira.","ai_generated":true,"unit":"transfor-000041#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Transforma's methodology provides systematic, comparable information across the three stages of an energy community's life cycle—planning, construction, and operation—using a tool filled out by a community representative and a complementary household instrument.","ai_generated":true,"unit":"transfor-000041#insight-1","date_modified":"2026-10-23"},{"text":"The ICSI methodology focuses on deep socioeconomic analysis of specific territories, utilizing household surveys to document observable changes over a period of 12 to 18 months.","ai_generated":true,"unit":"transfor-000041#insight-2","date_modified":"2026-10-23"},{"text":"A pilot application of the ICSI tool in Tomarrazón, La Guajira, involving 218 beneficiary households, revealed that electricity service quality is inconsistent across the community and that there is a prevailing distrust of institutional energy information.","ai_generated":true,"unit":"transfor-000041#insight-3","date_modified":"2026-10-23"},{"text":"The two methodologies converge on three central analytical dimensions: energy service quality and coverage, community governance (the ability to manage collective resources), and energy literacy (user understanding and willingness to participate).","ai_generated":true,"unit":"transfor-000041#insight-4","date_modified":"2026-10-23"},{"text":"The document recommends prioritizing the joint application of these tools for communities transitioning between phases (e.g., from planning to construction) to better identify factors determining success or failure.","ai_generated":true,"unit":"transfor-000041#insight-5","date_modified":"2026-10-23"}],"climate_tags":["energy transition","energy poverty","public policy"],"geography_discussed":["La Guajira Department"],"frame_perspective":[],"analysis_type":["methodological framework","pilot study"]},{"id":"wri-000180","url":"https://climateinsightsdirectory.org/document/wri-000180","title":"Emissions and Environmental Surveys With Faith Actors: A Pilot Project With the Episcopal Church in the Philippines","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://www.wri.org/research/emissions-environmental-surveys-faith-actors-pilot-project-episcopal-church","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document details a pilot project involving the Episcopal Church in the Philippines (ECP) to measure GHG emissions across various assets. The survey categorized assets into five types—including churches and schools—and analyzed emissions from energy, water, waste, and refrigerants. Findings revealed that schools have the highest per-individual-asset emissions (153.78t), primarily from refrigerants, while churches have the lowest (6.31t), primarily from energy. The ECP intends to repeat the survey annually to track emission reduction targets. The paper also offers a step-by-step guide for other faith actors to adapt the model, recommending the use of asset inventories, internal communications, and coordinator training.","ai_generated":true,"unit":"wri-000180#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The pilot survey calculated GHG emissions across four sectors—energy, water, waste, and refrigerants—for five asset types, including churches, schools, and buildings.","ai_generated":true,"unit":"wri-000180#insight-1","date_modified":"2026-10-23"},{"text":"On a per-individual-asset basis, schools produced the highest emissions at 153.78t, with refrigerants being the primary contributor, whereas churches produced the lowest at 6.31t, with emissions driven mostly by energy consumption.","ai_generated":true,"unit":"wri-000180#insight-2","date_modified":"2026-10-23"},{"text":"A majority of Episcopal Church in the Philippines (ECP) assets already employ emission reduction and mitigation strategies, specifically reducing electricity consumption, harvesting rain water, tree-planting, and raising environmental awareness.","ai_generated":true,"unit":"wri-000180#insight-3","date_modified":"2026-10-23"},{"text":"The ECP intends to integrate the survey into its annual parochial reports by rerunning the measurement process every year.","ai_generated":true,"unit":"wri-000180#insight-4","date_modified":"2026-10-23"},{"text":"Recommendations for other faith actors adopting the survey tool include conducting training for survey coordinators, establishing an asset inventory, ensuring adequate resources, and initiating early internal communications.","ai_generated":true,"unit":"wri-000180#insight-5","date_modified":"2026-10-23"}],"climate_tags":["greenhouse gas emissions","climate change mitigation","greenhouse gas emissions reduction","refrigerant","waste management"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["pilot study","case study"]},{"id":"wri-000322","url":"https://climateinsightsdirectory.org/document/wri-000322","title":"Using a Deep Learning Framework to Forecast Reservoir Water Availability in India","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://www.wri.org/research/using-deep-learning-framework-forecast-reservoir-water-availability-india","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"WRI introduces a deep learning model, the Bayesian long short-term memory sequence-to-sequence-to-sequence model, to provide near-real-time forecasts of reservoir water volumes for a 90-day period in India. The pilot project focused on 11 reservoirs supplying thermal coal power generation, achieving a coefficient of determination score of 92% for short-term (1-14 day) forecasts and 56% for long-term (15-90 day) forecasts. The tool is intended to flag drought-like conditions and support the transition to water-prudent power production, though it is not intended for reservoir management operations.","ai_generated":true,"unit":"wri-000322#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"WRI developed a near-real-time forecasting tool for reservoir water volumes over a 90-day horizon using a Bayesian long short-term memory sequence-to-sequence-to-sequence deep learning framework and global meteorological data.","ai_generated":true,"unit":"wri-000322#insight-1","date_modified":"2026-10-23"},{"text":"A pilot study of 11 Indian reservoirs that provide water for thermal coal power generation showed the model's accuracy varied by timeframe, with a coefficient of determination score of 92% for 1-14 day forecasts and 56% for 15-90 day forecasts.","ai_generated":true,"unit":"wri-000322#insight-2","date_modified":"2026-10-23"},{"text":"The forecast is intended to help avoid acute power outages caused by insufficient cooling water supply and to support water-prudent policies, but it is explicitly not for use in reservoir management operations.","ai_generated":true,"unit":"wri-000322#insight-3","date_modified":"2026-10-23"}],"climate_tags":["drought","climate change"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["predictive modelling","pilot study"]},{"id":"wri-001098","url":"https://climateinsightsdirectory.org/document/wri-001098","title":"How to Identify Degraded Land for Sustainable Palm Oil in Indonesia","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"research paper","language":"id","date_published":null,"source_url":"https://www.wri.org/research/how-identify-degraded-land-sustainable-palm-oil-indonesia","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document presents a methodology for identifying potentially suitable degraded land for sustainable palm oil in Indonesia, specifically applied in West and Central Kalimantan. The approach uses a two-step process: a desktop analysis based on environmental, economic, social, and legal indicators, followed by rapid field assessments. This method is designed to align with RSPO standards, Indonesian law, and national REDD+ strategies. In a pilot application in West Kalimantan under Project POTICO, the method helped identify nine potentially suitable areas. Across West and Central Kalimantan, the initial desktop analysis identified approximately seven million hectares of potentially suitable land.","ai_generated":true,"unit":"wri-001098#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The proposed identification method consists of a desktop analysis using available data and rapid field assessments, incorporating indicators related to legal, social, economic, and environmental factors.","ai_generated":true,"unit":"wri-001098#insight-1","date_modified":"2026-10-23"},{"text":"The methodology is designed to be consistent with Indonesian laws, national REDD+ strategies for low carbon degraded land, and sustainable production standards such as those from the Roundtable on Sustainable Palm Oil (RSPO).","ai_generated":true,"unit":"wri-001098#insight-2","date_modified":"2026-10-23"},{"text":"A desktop analysis applied to the provinces of West Kalimantan and Central Kalimantan identified approximately seven million hectares of land as potentially suitable for oil palm cultivation.","ai_generated":true,"unit":"wri-001098#insight-3","date_modified":"2026-10-23"},{"text":"In a pilot application for Project POTICO in West Kalimantan, the method was used to identify nine potentially suitable areas through field assessments of high-priority sites identified via desktop analysis.","ai_generated":true,"unit":"wri-001098#insight-4","date_modified":"2026-10-23"},{"text":"The method is intended as a first step to reduce costs for further due diligence; it is not meant to predetermine expansion sites and must be followed by activities such as high conservation value (HCV) assessments, social impact assessments, and free prior and informed consent (FPIC) processes.","ai_generated":true,"unit":"wri-001098#insight-5","date_modified":"2026-10-23"}],"climate_tags":["Reducing emissions from deforestation and forest degradation","Free, Prior and Informed Consent"],"geography_discussed":["West Kalimantan","Central Kalimantan"],"frame_perspective":[],"analysis_type":["methodology demonstration","pilot study"]},{"id":"wwf-000212","url":"https://climateinsightsdirectory.org/document/wwf-000212","title":"No Food Left Behind Growers’ Perspective on Measuring Fresh Produce Left in the Field: A Summary Business Case","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"executive summary","language":"en","date_published":null,"source_url":"https://www.worldwildlife.org/documents/605/1dyzojtuj0_WWF_NoFoodLeftBehind_PART5.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The document argues that measuring on-farm food loss is a low-cost, resource-efficient process that provides growers with data to improve operational efficiency and identify new markets for edible but unmarketable produce. Based on a 2021 pilot with seven growers in the US, it highlights that food loss is often driven by strict retail specifications, labor costs, and market dynamics. The SISC Food Loss Metric tool allows growers to categorize unharvested crops as marketable, edible but not marketable, or inedible, with the sampling process taking approximately one hour for two people. The report concludes that while growers see the value in this data, systemic change requires buyers and policymakers to create financial incentives and new sales channels for 'ugly' or surplus produce.","ai_generated":true,"unit":"wwf-000212#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Global food loss on farms is estimated to be as high as 1.3 billion tons, which represents nearly 15% of all food produced.","ai_generated":true,"unit":"wwf-000212#insight-1","date_modified":"2026-10-23"},{"text":"Several systemic factors drive the loss of produce on farms, including strict retail quality specifications, labor shortages, high labor costs, unpredictable weather, and inflexible short-term contracts.","ai_generated":true,"unit":"wwf-000212#insight-2","date_modified":"2026-10-23"},{"text":"The SISC Food Loss Metric tool provides a low-cost method for growers to track crops that reached maturity but did not enter the human consumption supply chain, categorizing them as marketable, edible but not marketable, or inedible.","ai_generated":true,"unit":"wwf-000212#insight-3","date_modified":"2026-10-23"},{"text":"Pilot participants found that in-field measurement is not resource-intensive; sampling and data collection typically take about one hour for two people, with sorting and analysis taking an additional 1 to 1.5 hours.","ai_generated":true,"unit":"wwf-000212#insight-4","date_modified":"2026-10-23"},{"text":"Growers use the resulting data to improve internal operations, such as assessing workforce performance, refining planting schedules to avoid 'pile-ups', and identifying potential secondary markets for cosmetically imperfect produce.","ai_generated":true,"unit":"wwf-000212#insight-5","date_modified":"2026-10-23"},{"text":"Growers indicate that they lack the financial incentive to measure or harvest edible surplus unless there is a direct request from a major customer or a clear economic reward, as harvesting at a loss is not viable given rising input costs.","ai_generated":true,"unit":"wwf-000212#insight-6","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["California","Hawaii","Virginia"],"frame_perspective":[],"analysis_type":["business case","pilot study","executive summary"]}]}