{"query_echo":{"q":"","filters":{"geography":["Oceania"]},"warnings":[]},"total":{"value":47,"relation":"eq"},"page":2,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?geography=Oceania&page=2","next":"https://climateinsightsdirectory.org/api/v1/search?geography=Oceania&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":"ember-000205","url":"https://climateinsightsdirectory.org/document/ember-000205","title":"Asia Data Transparency Report 2023","publisher":{"name":"Ember","organization":"ember"},"document_type":"report","language":"en","date_published":"2023-05-04","source_url":"https://ember-energy.org/app/uploads/2024/10/Asia-Data-Transparency-2023-PDF-4-MB.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The Asia Data Transparency Report 2023 finds that over half of the surveyed Asian economies have poor or insufficient power sector data transparency, affecting the electricity needs of 684 million people. While high-income economies generally score better, some lower-middle income nations like India, Bangladesh, and Sri Lanka are demonstrating good practice. The report emphasizes that granular, real-time, and open-access data is essential for grid optimization and evidence-based policymaking to meet decarbonisation targets. It highlights a successful public-private partnership in India between NITI Aayog and the Vasudha Foundation and provides nine practical recommendations for improving data governance, including the use of machine-readable formats and unique identifiers.","ai_generated":true,"unit":"ember-000205#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"More than half of the assessed economies in Asia exhibit poor or insufficient data transparency, which corresponds to the electricity demand and supply for 684 million people.","ai_generated":true,"unit":"ember-000205#insight-1","date_modified":"2026-10-23"},{"text":"Six economies are identified as demonstrating good practice in data transparency, scoring 'good' or 'excellent': India, Sri Lanka, Bangladesh, South Korea, Australia, and New Zealand.","ai_generated":true,"unit":"ember-000205#insight-2","date_modified":"2026-10-23"},{"text":"Asian economies generally perform poorly regarding publishing lag, geographical granularity, and time granularity, while scoring better on fuel breakdown and ease of access.","ai_generated":true,"unit":"ember-000205#insight-3","date_modified":"2026-10-23"},{"text":"High-quality temporal granularity is rare; only seven economies (Japan, Australia, Bangladesh, Singapore, New Zealand, Sri Lanka, and Georgia) provide hourly data, which is necessary for managing renewable energy intermittency.","ai_generated":true,"unit":"ember-000205#insight-4","date_modified":"2026-10-23"},{"text":"Data accessibility is hindered by the use of non-machine-readable formats, with one third of economies providing data as PDFs or scanned images.","ai_generated":true,"unit":"ember-000205#insight-5","date_modified":"2026-10-23"},{"text":"India has improved its data transparency through a partnership between the government think tank NITI Aayog and the non-profit Vasudha Foundation to create a 'one-stop shop' open access data platform.","ai_generated":true,"unit":"ember-000205#insight-6","date_modified":"2026-10-23"},{"text":"The report recommends nine specific improvements for data transparency, including the adoption of machine-readable formats (xlsx, csv, json), the removal of access restrictions, and the implementation of unique identifiers for power plants.","ai_generated":true,"unit":"ember-000205#insight-7","date_modified":"2026-10-23"}],"climate_tags":["Grid decarbonization","renewable energy","grid flexibility","emission intensity","electricity generation","carbon neutrality"],"geography_discussed":["India","Australia","New Zealand","South Korea","Bangladesh","Sri Lanka","People's Republic of China","Japan","Indonesia","Vietnam","Thailand","Malaysia","Pakistan","Philippines","Singapore","Myanmar","Taiwan","Kazakhstan","Uzbekistan","Hong Kong","Azerbaijan"],"frame_perspective":[],"analysis_type":["regional assessment","case study","policy recommendations"]},{"id":"geconco-000105","url":"https://climateinsightsdirectory.org/document/geconco-000105","title":"Mapping the Global Youth Climate Movement","publisher":{"name":"Green Economy Coalition","organization":"green-economy-coalition"},"document_type":"report","language":"en","date_published":"2023-02","source_url":"https://www.greeneconomycoalition.org/assets/reports/GEC-Reports/YCM-2023/Mapping-the-Global-YCM-March23-FINAL.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report maps the global youth climate movement (YCM), finding a strong consensus that capitalism and colonialism are the root causes of the climate crisis, yet a significant lack of coherent theories of change to translate this analysis into systemic transformation. While many groups remain wedded to reformist tactics like school strikes, an emerging 'Radical Green' wing is developing strategic fluency. The movement faces critical gaps in funding, organisational structure, and vision-building, particularly in the post-pandemic landscape.","ai_generated":true,"unit":"geconco-000105#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"A majority of the youth climate movement (YCM) agrees on a systemic analysis of the climate crisis, with 54% of surveyed groups identifying \"a system that puts profit over people and planet\" as the root cause. Among these, 89% specifically name capitalism and (neo-)colonialism as the drivers of ecological breakdown.","ai_generated":true,"unit":"geconco-000105#insight-1","date_modified":"2026-10-23"},{"text":"Despite agreement on root causes, the YCM lacks a coherent, shared theory of change. Many groups exhibit strategic incoherence, such as identifying the system as the root cause but pursuing visions of new political leadership or missions of general environmental awareness.","ai_generated":true,"unit":"geconco-000105#insight-2","date_modified":"2026-10-23"},{"text":"There is a significant 'vision breakdown' where groups fail to translate their systemic analysis into a vision for structural change. This is attributed to a lack of deep analysis regarding how capitalism operates and a 'strategic dogma' in some groups, such as those committed to the Fridays For Future (FFF) model of school strikes and demanding leaders 'listen to the science'.","ai_generated":true,"unit":"geconco-000105#insight-3","date_modified":"2026-10-23"},{"text":"The report identifies a 'radical education effect,' particularly in regions like West Africa, where groups use environmental education not as an end in itself, but as a prerequisite to build the radical consciousness necessary for green economic transformation.","ai_generated":true,"unit":"geconco-000105#insight-4","date_modified":"2026-10-23"},{"text":"An emerging 'Radical Green' wing of the YCM is demonstrating 'strategic fluency,' moving beyond aesthetics to develop concrete plans for ruptural change, including engaging fossil-dependent communities and forming coalitions with workers and unions.","ai_generated":true,"unit":"geconco-000105#insight-5","date_modified":"2026-10-23"},{"text":"The YCM requires substantial support to increase its impact, most notably in funding. This includes operational support for basic maintenance, project-based funding for international coordination, and core funding for activist salaries to reduce reliance on volunteers.","ai_generated":true,"unit":"geconco-000105#insight-6","date_modified":"2026-10-23"},{"text":"Beyond finance, the movement needs organisational development in three areas: establishing stable internal structures to prevent burnout, developing explicit movement strategies and policy research, and fostering higher levels of domestic and international networking.","ai_generated":true,"unit":"geconco-000105#insight-7","date_modified":"2026-10-23"},{"text":"The internet stocktake identified 292 youth climate groups globally, noting that Africa appears to have the most vibrant movement in terms of the number of groups identified, survey completion rates, and responsiveness to interviews.","ai_generated":true,"unit":"geconco-000105#insight-8","date_modified":"2026-10-23"}],"climate_tags":["climate justice","environmental education","climate policy","climate finance"],"geography_discussed":["Africa","Europe","North America","South America","Asia","Oceania"],"frame_perspective":[],"analysis_type":["mapping","strategic assessment","qualitative analysis"]},{"id":"rmi-000743","url":"https://climateinsightsdirectory.org/document/rmi-000743","title":"Dejemos de quemar dinero","publisher":{"name":"RMI","organization":"rmi"},"document_type":"report","language":"es","date_published":"2023-02","source_url":"https://rmi.org/app/uploads/2023/02/dejemos_de_quemar_dinero.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report argues that the Dominican Republic can eliminate its annual US$2 billion electricity subsidy by investing 2.5 to 3 years' worth of those funds (US$4.5 to US$6 billion) into rooftop solar installations. Using a blended finance approach—combining government grants with local loans—the model aims to reduce household electricity costs by up to 90% over time while ending the government's reliance on volatile fossil fuel expenditures.","ai_generated":true,"unit":"rmi-000743#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The Dominican Republic government spends approximately US$2 billion annually on electricity subsidies to mitigate fuel costs, representing 11% of its 2023 annual budget to support nearly 2.8 million households.","ai_generated":true,"unit":"rmi-000743#insight-1","date_modified":"2026-10-23"},{"text":"A proposed blended finance model suggests that investing between US$4.5 billion and US$6 billion (equivalent to 2.5 to 3 years of subsidies) into rooftop solar for residential homes and small businesses could permanently eliminate the need for electricity subsidies.","ai_generated":true,"unit":"rmi-000743#insight-2","date_modified":"2026-10-23"},{"text":"For a typical low-to-middle income household consuming 200 kWh/month, a rooftop solar system costing US$2,400—funded by a US$1,330 government grant and a US$1,070 loan—could reduce electricity costs by 15-25% during the loan repayment period and by 90% once the loan is paid off.","ai_generated":true,"unit":"rmi-000743#insight-3","date_modified":"2026-10-23"},{"text":"The 'RD 100% Renovable' coalition, which includes the government and local entities, has committed to installing 600 MW of rooftop solar in the Dominican Republic using this blended finance model, targeting 200,000 households and small businesses.","ai_generated":true,"unit":"rmi-000743#insight-4","date_modified":"2026-10-23"}],"climate_tags":["fossil fuel subsidy","rooftop photovoltaic system","Blended Finance","energy transition","energy independence","carbon dioxide emissions","renewable energy","electricity price"],"geography_discussed":["Puerto Rico","Africa","Middle East","Oceania","Caribbean"],"frame_perspective":[],"analysis_type":["policy proposal","financial modeling"]},{"id":"seforall-000337","url":"https://climateinsightsdirectory.org/document/seforall-000337","title":"ANNUAL MONITORING REVIEW 2023","publisher":{"name":"Sustainable Energy for All","organization":"sustainable-energy-for-all"},"document_type":"executive summary","language":"en","date_published":"2023","source_url":"https://www.seforall.org/system/files/2024-09/SEforALL-annual-monitoring-review-executive-summary-2023u.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The 2023 Annual Monitoring Review marks the conclusion of SEforALL's 2021-2023 Business Plan, reporting the overachievement of cross-organizational KPIs. Key results include the mobilization of over USD 8 billion towards energy access and clean energy transitions, the facilitation of 26,669 new energy access connections, and the support of 31 countries in 2023. The report details achievements across four thematic areas: Energy Diplomacy and Advocacy, Energy Access and Closing the Gap, Energy Transitions and Climate, and the Intersection with other SDGs. Notable outcomes include the spearheading of UN Energy Compacts with USD 1.3 trillion in commitments and the deployment of the Universal Energy Facility (UEF) in five countries.","ai_generated":true,"unit":"seforall-000337#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"SEforALL overachieved its cross-organizational KPIs for the 2021-2023 Business Plan cycle, including the mobilization of more than USD 8 billion towards energy access and clean energy transitions.","ai_generated":true,"unit":"seforall-000337#insight-1","date_modified":"2026-10-23"},{"text":"In 2023, SEforALL provided active support to 31 countries, 26 of which are Official Development Assistance (ODA)-recipient countries. These 26 countries represent 53 percent of the global population without electricity access and 49 percent of the population lacking clean cooking fuels and technologies.","ai_generated":true,"unit":"seforall-000337#insight-2","date_modified":"2026-10-23"},{"text":"The organization facilitated 26,669 new energy access connections by the end of 2023, with 21,714 connections achieved indirectly and 4,955 achieved directly.","ai_generated":true,"unit":"seforall-000337#insight-3","date_modified":"2026-10-23"},{"text":"Through the UN Energy Compacts, SEforALL helped capture voluntary SDG7 commitments totaling USD 1.3 trillion, contributing to 129 million people gaining new or improved electricity connections and 22 million gaining enhanced clean cooking access.","ai_generated":true,"unit":"seforall-000337#insight-4","date_modified":"2026-10-23"},{"text":"The Universal Energy Facility (UEF) raised over USD 40 million to support mini-grid and stand-alone solar systems in Benin, the Democratic Republic of Congo, Madagascar, Nigeria, and Sierra Leone, achieving over 4,900 connections and disbursing USD 5.3 million by the end of 2023.","ai_generated":true,"unit":"seforall-000337#insight-5","date_modified":"2026-10-23"},{"text":"SEforALL developed four Energy Transition and Investment Plans (ETIPs) for Barbados, Ghana, Kenya, and Nigeria. In Nigeria specifically, the Energy Transition Office (ETO) helped mobilize approximately USD 6.09 billion in investments.","ai_generated":true,"unit":"seforall-000337#insight-6","date_modified":"2026-10-23"},{"text":"The organization's advocacy influenced the global climate agenda at COP28, resulting in seven critical changes to the global stocktake decision text and the announcement of USD 3.5 billion in financial commitments for just and equitable energy transitions.","ai_generated":true,"unit":"seforall-000337#insight-7","date_modified":"2026-10-23"},{"text":"In the area of healthcare electrification, SEforALL supported the electrification of 935 health facilities since 2020 and powered six hospitals in Sierra Leone using solar and battery storage, benefiting over 8.5 million people.","ai_generated":true,"unit":"seforall-000337#insight-8","date_modified":"2026-10-23"},{"text":"SEforALL's gender and youth initiatives supported 487 women in the sustainable energy sector, including 261 who received technical training and 60 who were supported to speak at leading industry events.","ai_generated":true,"unit":"seforall-000337#insight-9","date_modified":"2026-10-23"}],"climate_tags":["energy access","energy transition","clean cooking","Mini-grids","solar energy","energy efficiency","carbon neutrality","greenhouse gas emissions","carbon emission trading","climate finance"],"geography_discussed":["Kenya","Ghana","Barbados","Sierra Leone","Madagascar","Benin","Congo, Dem. Rep.","Rwanda","Malawi","Africa","Asia","Latin America and the Caribbean","Oceania"],"frame_perspective":[],"analysis_type":["monitoring and evaluation","impact assessment"]},{"id":"climcent-000309","url":"https://climateinsightsdirectory.org/document/climcent-000309","title":"365 Days on a Warming Planet","publisher":{"name":"Climate Central","organization":"climate-central"},"document_type":"report","language":"en","date_published":"2022-10","source_url":"https://assets.ctfassets.net/cxgxgstp8r5d/2XzrYheK2B1zL0a1sPOgp3/b9e096a1b338401fe30401e8b9f3fd85/Climate_Central_Report_365_Days_on_a_Warming_Planet.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"Climate Central's global analysis using the Climate Shift Index (CSI) found that 96% of the world's population—7.6 billion people—experienced daily temperatures made warmer by human-caused climate change between October 2021 and September 2022. The study identifies the strongest influences in regions near the equator and on small islands, with Lagos, Mexico City, and Singapore emerging as the highest hotspots of human exposure when accounting for urban population. The analysis also pinpointed peak continental CSI days, noting that these do not always coincide with major heat waves.","ai_generated":true,"unit":"climcent-000309#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Human-caused climate change affected the temperatures experienced by 7.6 billion people, representing approximately 96% of the global population, during the 12-month study period from October 1, 2021, to September 30, 2022.","ai_generated":true,"unit":"climcent-000309#insight-1","date_modified":"2026-10-23"},{"text":"The strongest influence of human-driven warming was observed in Mexico, Brazil, the Arabian Peninsula, the Malay Archipelago, and western and eastern Africa.","ai_generated":true,"unit":"climcent-000309#insight-2","date_modified":"2026-10-23"},{"text":"Global exposure to temperatures made at least three times more likely due to climate change peaked on October 9, 2021, affecting more than 1.7 billion people.","ai_generated":true,"unit":"climcent-000309#insight-3","date_modified":"2026-10-23"},{"text":"When accounting for urban population size, the highest total human exposure to daily temperatures altered by climate change occurred in Lagos, Nigeria; Mexico City, Mexico; and Singapore.","ai_generated":true,"unit":"climcent-000309#insight-4","date_modified":"2026-10-23"},{"text":"Cities in small island developing states exhibited the highest average CSI scores, with Apia, Samoa and Ngerulmud, Palau ranking as the top two cities.","ai_generated":true,"unit":"climcent-000309#insight-5","date_modified":"2026-10-23"},{"text":"The analysis identified specific peak CSI days for each continent: Oceania (October 19, 2021), Africa (November 25, 2021), Europe (February 17, 2022), South America (July 16, 2022), North America (July 19, 2022), and Asia (August 9, 2022).","ai_generated":true,"unit":"climcent-000309#insight-6","date_modified":"2026-10-23"},{"text":"The report notes that peak continental CSI days do not necessarily align with major heat waves; for example, Europe's peak CSI influence was more widespread in February than during the July 2022 heat wave.","ai_generated":true,"unit":"climcent-000309#insight-7","date_modified":"2026-10-23"}],"climate_tags":["extreme event attribution","climate change"],"geography_discussed":["Mexico","Brazil","Africa","Arabian Peninsula","Malay Archipelago","Lagos","Mexico City","Singapore","Oceania","Europe","Asia","North America","South America","Samoa","Palau"],"frame_perspective":[],"analysis_type":["attribution analysis","statistical modeling"]},{"id":"wwf-000572","url":"https://climateinsightsdirectory.org/document/wwf-000572","title":"Measuring and Mitigating GHGs: Beef","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"research paper","language":"en","date_published":"2022-09-18","source_url":"https://www.worldwildlife.org/documents/108/5dhaztmhjq_MOBERG_GHG_Brief_BEEF_06_22_v3.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report examines the greenhouse gas (GHG) footprint of beef production, highlighting that emissions vary drastically by region and production system, ranging from 16 to 360 kg CO2e/kg edible meat. It identifies enteric fermentation, feed production, and land-use change as the primary emission drivers, while noting that well-managed grazing lands can act as carbon sinks. The document outlines mitigation strategies including improved feed digestibility, rotational grazing, and feed additives, estimating a total global mitigation potential between 0.67 and 2.55 GtCO2e/yr.","ai_generated":true,"unit":"wwf-000572#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Beef has the highest average global emissions intensity per kilogram of all meats, with over 80% of these emissions occurring during the production phase. Global estimates for GHG emissions range from 16 to 360 kg CO2e/kg edible weight (EW), with an average of approximately 76 kg CO2e/kg EW.","ai_generated":true,"unit":"wwf-000572#insight-1","date_modified":"2026-10-23"},{"text":"Emissions vary significantly by production system: grass-based systems average 95 kg CO2e/kg EW, mixed farming systems average 58 kg CO2e/kg EW, and cattle in feedlots produce meat at 21 kg CO2e/kg EW. Beef from beef herds generally has higher GHG intensity than beef from dairy herds, as dairy emissions are shared with milk production.","ai_generated":true,"unit":"wwf-000572#insight-2","date_modified":"2026-10-23"},{"text":"Feed and land-use change (LUC) are major emission drivers. In Latin America, over half of the emissions from grassland cattle feed (25 kg CO2e/kg EW) result from pasture expansion. Global LUC for cattle is a significant source, contributing between 0.39 and 1.65 GtCO2e/yr depending on the estimation model used.","ai_generated":true,"unit":"wwf-000572#insight-3","date_modified":"2026-10-23"},{"text":"Enteric fermentation is a primary source of methane, with global intensity estimated between 22-26 kg CO2e/kg EW. These emissions vary by geography, ranging from 11 kg CO2e/kg EW in Eastern Europe to 76 kg CO2e/kg EW in South Asia, driven by factors such as feed digestibility and animal age at slaughter.","ai_generated":true,"unit":"wwf-000572#insight-4","date_modified":"2026-10-23"},{"text":"Grazing lands have the potential for carbon sequestration, which can mitigate overall emissions. Global mitigation potential for soil carbon sequestration in beef grazing systems is estimated at 0.04-0.8 GtCO2/yr, with specific rates in the US Northern Great Plains between 0.4 and 0.5 tC/ha/yr.","ai_generated":true,"unit":"wwf-000572#insight-5","date_modified":"2026-10-23"},{"text":"The total global carbon mitigation potential for beef production is estimated between 0.67 and 2.55 GtCO2e/yr. The highest potential gains come from improved grazing management, improved feed digestibility, and avoided land-use change through intensification.","ai_generated":true,"unit":"wwf-000572#insight-6","date_modified":"2026-10-23"}],"climate_tags":["greenhouse gas emissions","methane","nitrous oxide","carbon sequestration","land-use change","deforestation"],"geography_discussed":["Asia","Latin America","Africa","North America","Europe","Oceania","United States","Brazil","European Union","Russia","Argentina","Eastern Europe","South Asia","sub-Saharan Africa","People's Republic of China","India","Zambia"],"frame_perspective":[],"analysis_type":["life cycle assessment","mitigation assessment"]},{"id":"clipolin-000886","url":"https://climateinsightsdirectory.org/document/clipolin-000886","title":"The Landscape of Methane Abatement Finance","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"executive summary","language":"en","date_published":"2022-07","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2022/07/Summary-l-Landscape-of-Methane-Abatement-Finance.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that targeted methane abatement finance is severely underfunded, representing less than 2% of total climate finance at USD 11.6 billion in 2019/2020. Despite the high mitigation potential and availability of low-cost technologies, particularly in the fossil fuel sector, investment is disproportionately concentrated in the waste sector. The authors argue that a tenfold increase in annual finance is required to meet the estimated USD 119 billion needed to keep warming under +2C.","ai_generated":true,"unit":"clipolin-000886#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Targeted methane abatement finance is critically insufficient, totaling USD 11.6 billion in 2019/2020, which is less than 2% of total climate finance flows. To keep global warming under +2C, an estimated USD 119 billion is needed annually through 2050, necessitating at least a tenfold increase in current funding.","ai_generated":true,"unit":"clipolin-000886#insight-1","date_modified":"2026-10-23"},{"text":"There is a significant misalignment between methane mitigation potential and financial allocation. The fossil fuel sector has the highest potential for mitigation by 2030 but received the lowest amount of finance, representing less than 0.5% of total methane abatement funding (USD 0.1 billion), far below the estimated annual need of USD 31.6 billion through 2050.","ai_generated":true,"unit":"clipolin-000886#insight-2","date_modified":"2026-10-23"},{"text":"The waste sector received the majority of targeted methane abatement finance in 2019/2020, totaling USD 7.3 billion. Much of this was directed toward waste-to-energy projects, specifically waste incinerators which accounted for USD 4.6 billion, although these can generate significant CO2 emissions.","ai_generated":true,"unit":"clipolin-000886#insight-3","date_modified":"2026-10-23"},{"text":"The AFOLU sector attracted USD 4.3 billion in annual targeted finance in 2019/2020, significantly below the estimated annual need of USD 43.2 billion through 2050. Over half of these investments focused on bioenergy projects using forestry and crop residues, while specific solutions for livestock enteric fermentation and rice paddies remain underserved.","ai_generated":true,"unit":"clipolin-000886#insight-4","date_modified":"2026-10-23"},{"text":"Geographically, methane abatement finance is concentrated in the East Asia and Pacific region, which received USD 6.0 billion (over 50% of tracked finance). In contrast, South Asia and Latin America & Caribbean combined produced 28% of methane emissions but received only 5% of tracked finance.","ai_generated":true,"unit":"clipolin-000886#insight-5","date_modified":"2026-10-23"},{"text":"Private sector financial flows accounted for USD 6.2 billion of the tracked finance, primarily in commercially viable segments like waste-to-energy. The public sector contributed USD 4.5 billion, with Development Finance Institutions (DFIs) providing USD 1.5 billion (13% of total flows), playing a critical role in the AFOLU sector.","ai_generated":true,"unit":"clipolin-000886#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate finance","fossil fuel industry","waste-to-energy","bioenergy","carbon offset"],"geography_discussed":["East Asia and Pacific","People's Republic of China","South Asia","Latin America & Caribbean","US & Canada","Central Asia and Eastern Europe","Western Europe","Middle East & North Africa","sub-Saharan Africa","Oceania"],"frame_perspective":[],"analysis_type":["financial analysis","sectoral assessment","geographic analysis"]},{"id":"clipolin-001165","url":"https://climateinsightsdirectory.org/document/clipolin-001165","title":"Landscape of Climate Finance for Agriculture, Forestry, Other Land Uses and Fisheries","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"report","language":"en","date_published":"2022","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2022/11/Landscape-of-Climate-Finance-for-Agriculture-Forestry-Other-Land-Uses-and-Fisheries.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that climate finance for AFOLU sectors is severely underfunded, representing only 2.5% of total tracked climate finance in 2019/20. While overall trends were positive between 2013 and 2020, a 20% drop occurred between 2017/18 and 2019/20. The sectors require an estimated USD 423.4 billion annually by 2030 to align with the Paris Agreement, a nearly 26-fold increase over 2019/20 levels. Finance is dominated by public sources, with significant gaps in private investment and a stagnation in adaptation funding. Geographically, East Asia and the Pacific are the primary recipients, followed by Sub-Saharan Africa.","ai_generated":true,"unit":"clipolin-001165#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Climate finance for AFOLU sectors is significantly lower than in other sectors and experienced a recent decline. In 2019/20, AFOLU received only 2.5% of total tracked climate finance, compared to 51% for renewable energy generation and nearly 26% for low-carbon transport. While the general trend from 2013 to 2020 was positive, there was a 20% drop between 2017/18 and 2019/20, with the latter period averaging USD 16.3 billion.","ai_generated":true,"unit":"clipolin-001165#insight-1","date_modified":"2026-10-23"},{"text":"There is a massive gap between current funding and the investment needed for a Paris-compatible trajectory. AFOLU sectors require an average of USD 423.4 billion per year up to 2030, which is a nearly 26-fold increase over the 2019/20 annual average of USD 16.3 billion.","ai_generated":true,"unit":"clipolin-001165#insight-2","date_modified":"2026-10-23"},{"text":"Climate finance for AFOLU is overwhelmingly provided by public sources, while private investment remains very low. Private finance only passed the 1% threshold for the first time in 2019/20, lagging far behind the cross-sector average where 49% of total climate finance originates from private sources. Barriers to private investment include high actual and perceived risks, long pay-back periods, and low returns.","ai_generated":true,"unit":"clipolin-001165#insight-3","date_modified":"2026-10-23"},{"text":"Funding for climate mitigation has increased significantly, but adaptation finance has plateaued. Mitigation finance rose from a USD 3 billion annual average in 2015/16 to USD 10.6 billion in 2017/18. Adaptation finance, which makes up 34% of AFOLU climate finance (compared to 7.4% across all sectors), has fluctuated mildly and dropped in 2019/20.","ai_generated":true,"unit":"clipolin-001165#insight-4","date_modified":"2026-10-23"},{"text":"Geographically, the East Asia and Pacific region is the largest recipient of AFOLU climate finance (39%), followed by Sub-Saharan Africa (24%). In Sub-Saharan Africa, AFOLU attracts substantive investment due to its economic importance, as agriculture accounts for 23% of the region's GDP.","ai_generated":true,"unit":"clipolin-001165#insight-5","date_modified":"2026-10-23"},{"text":"Investment is heavily concentrated in forestry and agriculture, which together received nearly 80% of AFOLU climate finance in 2019/20. Other areas, such as fisheries, food loss and waste, and low-carbon diets, each represent a minor fraction of less than 1% of tracked finance.","ai_generated":true,"unit":"clipolin-001165#insight-6","date_modified":"2026-10-23"}],"climate_tags":["agriculture","forestry","climate finance","climate change mitigation","climate change adaptation","Blended Finance","Climate-smart agriculture","Paris Agreement"],"geography_discussed":["East Asia and Pacific","sub-Saharan Africa","United States","Canada","Australia","Oceania","Western Europe","Eastern Europe","Central Asia"],"frame_perspective":[],"analysis_type":["financial analysis","trend analysis","gap analysis"]},{"id":"clipolin-001114","url":"https://climateinsightsdirectory.org/document/clipolin-001114","title":"Global Landscape of Climate Finance 2021","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"report","language":"en","date_published":"2021-12","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2021/10/Full-report-Global-Landscape-of-Climate-Finance-2021.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The Global Landscape of Climate Finance 2021 reports that annual climate finance reached USD 632 billion in 2019/2020, though growth has slowed. The report highlights a massive investment gap, noting that an increase of at least 590% is needed to meet 2030 climate objectives. Mitigation remains the dominant focus, particularly in renewable energy and low-carbon transport, while adaptation finance continues to lag, relying almost entirely on public sources. Geographically, investments are heavily concentrated in East Asia & Pacific, Western Europe, and North America, with China accounting for an estimated 81% of investments in its region.","ai_generated":true,"unit":"clipolin-001114#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Total annual climate finance reached USD 632 billion in 2019/2020, but the growth rate has slowed to 10% between 2017/2018 and 2019/2020, compared to over 24% in previous periods.","ai_generated":true,"unit":"clipolin-001114#insight-1","date_modified":"2026-10-23"},{"text":"Current climate finance levels are insufficient, with an estimated annual need of USD 4.5 to 5 trillion to achieve a sustainable, net zero emissions and resilient world.","ai_generated":true,"unit":"clipolin-001114#insight-2","date_modified":"2026-10-23"},{"text":"Adaptation finance increased by 53% to USD 46 billion in 2019/2020, yet it represents only 7% of total climate finance and is provided almost exclusively by the public sector.","ai_generated":true,"unit":"clipolin-001114#insight-3","date_modified":"2026-10-23"},{"text":"Public climate finance averaged USD 321 billion in 2019/2020, with Development Finance Institutions (DFIs) contributing the majority at 68% (USD 219 billion).","ai_generated":true,"unit":"clipolin-001114#insight-4","date_modified":"2026-10-23"},{"text":"Private climate investments rose to USD 310 billion in 2019/2020, with commercial financial institutions showing the most growth, increasing their share from 18% to 39% (USD 122 billion).","ai_generated":true,"unit":"clipolin-001114#insight-5","date_modified":"2026-10-23"},{"text":"Debt was the primary financial instrument, accounting for 61% (USD 384 billion) of total finance, with market-rate debt making up 53% (USD 337 billion).","ai_generated":true,"unit":"clipolin-001114#insight-6","date_modified":"2026-10-23"},{"text":"Renewable energy investments averaged USD 324 billion, with solar PV and onshore wind attracting over 91% of all mitigation investment.","ai_generated":true,"unit":"clipolin-001114#insight-7","date_modified":"2026-10-23"},{"text":"Low-carbon transport is the fastest-growing sector, increasing by 23% compared to 2017/2018, with battery electric vehicles (BEVs) and chargers accounting for 48% of this finance.","ai_generated":true,"unit":"clipolin-001114#insight-8","date_modified":"2026-10-23"},{"text":"Approximately 75% of tracked climate investments (USD 479 billion) were domestic flows, while international flows reached USD 153 billion.","ai_generated":true,"unit":"clipolin-001114#insight-9","date_modified":"2026-10-23"},{"text":"Climate finance is highly concentrated, with East Asia & Pacific accounting for nearly half (USD 292 billion) of global investments, and 81% of that region's investment concentrated in China.","ai_generated":true,"unit":"clipolin-001114#insight-10","date_modified":"2026-10-23"}],"climate_tags":["climate finance","climate change adaptation","climate change mitigation","private investment","public finance","renewable energy","photovoltaics","onshore wind farm","offshore wind power","battery electric vehicle","energy efficiency","Blended Finance","equity","Sustainable Development Goals"],"geography_discussed":["East Asia & Pacific","People's Republic of China","Western Europe","United States","Canada","sub-Saharan Africa","South Asia","Latin America & Caribbean","Oceania"],"frame_perspective":[],"analysis_type":["financial analysis","geographic analysis","sectoral analysis"]},{"id":"clipolin-000287","url":"https://climateinsightsdirectory.org/document/clipolin-000287","title":"Private Financial Institutions Commitments to Paris Alignment","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"report","language":"en","date_published":"2021-10-18","source_url":"https://www.climatepolicyinitiative.org/publication/private-financial-institutions-commitments-to-paris-alignment/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The Climate Policy Initiative analyzed public climate commitments from over 350 private financial institutions across four sectors. While assets committed to net zero have grown to over USD 93 trillion, the report finds a significant lack of interim targets, detailed transition plans, and comprehensive fossil fuel phase-out strategies.","ai_generated":true,"unit":"clipolin-000287#summary","date_modified":"2026-08-17"},"key_insights":[{"text":"As of the report's release, at least 301 major financial institutions have committed to achieving net zero by 2050 at the latest, representing USD 93.3 trillion in financial assets. This reflects significant growth in 2021, with 65% of global assets under management and 17% of global financial assets now covered by such commitments.","ai_generated":true,"unit":"clipolin-000287#insight-1","date_modified":"2026-08-17"},{"text":"Despite the increase in net zero commitments, there is a lack of specific implementation details. Only 10% of entities with net zero targets have published public interim emission reduction targets, and none of the sampled entities provided details on the timing or method of using carbon offsets.","ai_generated":true,"unit":"clipolin-000287#insight-2","date_modified":"2026-08-17"},{"text":"Cumulative investments pledged to climate solutions by 2030 are tracked at almost USD 6 trillion, nearly double current private finance trends. However, these pledges often lack detail regarding target regions and sectors, and historically have not been directed toward hard-to-abate sectors or developing economies.","ai_generated":true,"unit":"clipolin-000287#insight-3","date_modified":"2026-08-17"},{"text":"Divestment and exclusion policies are primarily focused on coal, but often use broad thresholds that still allow for the financing of coal projects. There is a lack of a comprehensive global shift away from oil and gas financing, with most efforts limited to specific locations like tar sands or Arctic drilling.","ai_generated":true,"unit":"clipolin-000287#insight-4","date_modified":"2026-08-17"}],"climate_tags":["net zero","climate finance","divestment","carbon offsets","fossil fuel phase-out"],"geography_discussed":["Western Europe","United States","Canada","East Asia and Pacific","Latin America & Caribbean","Oceania","Middle East and North Africa","European Union","United Kingdom"],"frame_perspective":[],"analysis_type":["Tracking","Taxonomy development"]},{"id":"clipolin-001069","url":"https://climateinsightsdirectory.org/document/clipolin-001069","title":"Private Financial Institutions’ Commitments to Paris Alignment","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"report","language":"en","date_published":"2021-10","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2021/10/CPI_Private-FI-Commitments-Tracking-1.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that while net zero commitments from private financial institutions have grown rapidly, reaching USD 93.3 trillion in assets, they often lack the interim targets, detailed transition plans, and specificity in regional or sectoral investment needed for genuine Paris alignment. It highlights a strong focus on coal divestment but a significant lag in phasing out oil and gas financing and addressing biodiversity loss.","ai_generated":true,"unit":"clipolin-001069#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"As of October 11, 2021, at least 301 major financial institutions, representing USD 93.3 trillion in assets, have committed to achieving net zero emissions by 2050 at the latest. These commitments cover approximately 65% of global assets under management and 17% of the global financial industry.","ai_generated":true,"unit":"clipolin-001069#insight-1","date_modified":"2026-10-23"},{"text":"There is a significant lack of detailed implementation plans; only 10% of entities with net zero targets have published public interim emission reduction targets. Additionally, no entities in the sample provided details on the timing or methodology for using carbon offsets.","ai_generated":true,"unit":"clipolin-001069#insight-2","date_modified":"2026-10-23"},{"text":"Financial institutions have pledged nearly USD 6 trillion cumulatively to climate solutions by 2030, with commercial banks providing the vast majority at USD 5.6 trillion. However, these goals lack specificity regarding target regions and sectors, with USD 3.5 trillion allocated to a general \"green finance\" category.","ai_generated":true,"unit":"clipolin-001069#insight-3","date_modified":"2026-10-23"},{"text":"Fossil fuel exclusion policies are predominantly focused on coal, but a comprehensive shift away from all fossil fuels is missing. Many coal exclusions use broad revenue thresholds—ranging from 5% to 40%—that effectively allow continued financing of some coal projects.","ai_generated":true,"unit":"clipolin-001069#insight-4","date_modified":"2026-10-23"},{"text":"Commitments to exclude oil and gas are less than one-third of all fossil fuel exclusion announcements and are typically limited to specific high-risk areas like Arctic drilling and tar sands rather than a global reduction in new infrastructure.","ai_generated":true,"unit":"clipolin-001069#insight-5","date_modified":"2026-10-23"},{"text":"Commitments regarding biodiversity and deforestation are extremely sparse, with only four tracked commitments to exclude financing for activities contributing to deforestation and zero commitments on biodiversity.","ai_generated":true,"unit":"clipolin-001069#insight-6","date_modified":"2026-10-23"},{"text":"EU-27 institutions lead in the number of commitments, likely driven by the market size and the Sustainable Finance Disclosure Regulation (SFDR), which mandates climate risk disclosure.","ai_generated":true,"unit":"clipolin-001069#insight-7","date_modified":"2026-10-23"},{"text":"Financial institutions are adopting various business practices to meet goals, most notably the launch of new ESG-related products (28 of 69 tracked practices). Other internal changes include linking management compensation to sustainability ratings.","ai_generated":true,"unit":"clipolin-001069#insight-8","date_modified":"2026-10-23"}],"climate_tags":["Net-zero emissions","Paris Agreement","climate finance","fossil-fuel divestment","carbon offset","biodiversity","deforestation"],"geography_discussed":["Western Europe","United States","Canada","East Asia and Pacific","Latin America & Caribbean","Middle East and North Africa","Oceania","European Union","United Kingdom","Japan"],"frame_perspective":[],"analysis_type":["tracking","assessment"]},{"id":"wwf-000600","url":"https://climateinsightsdirectory.org/document/wwf-000600","title":"DRIVEN TO WASTE: THE GLOBAL IMPACT OF FOOD LOSS AND WASTE ON FARMS","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"report","language":"en","date_published":"2021","source_url":"https://www.worldwildlife.org/documents/1112/5p58sxloyr_technical_report_wwf_farm_stage_food_loss_and_waste.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that 15.3% of global agricultural production, approximately 1.2 billion tonnes, is lost at the farm stage, with an estimated economic value of $370 billion. It challenges the assumption that losses are primarily a low-income country issue, noting that higher- and middle-income countries are responsible for 58% of global harvest losses. Environmental impacts are significant, including 2.2 gigatonnes of CO2 eq. emissions, 760 km3 of freshwater withdrawals, and 4.4 million km2 of land use, with meat and animal products having a disproportionately high impact. The report identifies a complex web of direct drivers (biological, agronomic, and technological) and indirect drivers (market structure, governance, and human factors) and argues for synchronized, holistic interventions rather than isolated technical fixes.","ai_generated":true,"unit":"wwf-000600#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Global farm stage food losses are estimated at 1.2 billion tonnes per year, which represents 15.3% of total global food production. This is split between 8.3% lost at or around harvest and 7.0% during farm stage post-harvest activities.","ai_generated":true,"unit":"wwf-000600#insight-1","date_modified":"2026-10-23"},{"text":"The report challenges the assumption that farm stage losses are primarily a problem for low-income countries. Higher- and middle-income countries, representing 37% of the global population, account for 58% of global harvest losses, while low-income countries account for 54% of post-harvest farm stage losses.","ai_generated":true,"unit":"wwf-000600#insight-2","date_modified":"2026-10-23"},{"text":"The total economic value of global food losses at the farm gate is estimated at $370 billion per annum, excluding fisheries.","ai_generated":true,"unit":"wwf-000600#insight-3","date_modified":"2026-10-23"},{"text":"Farm stage food losses result in an annual carbon footprint of 2.2 gigatonnes CO2 eq., which is approximately 16% of total global emissions from agricultural production.","ai_generated":true,"unit":"wwf-000600#insight-4","date_modified":"2026-10-23"},{"text":"Meat and animal products (including dairy) have a disproportionately high environmental impact; they account for 40% of CO2 eq. emissions and over 40% of acidification and eutrophication potentials, despite representing only 13% of total food loss tonnage.","ai_generated":true,"unit":"wwf-000600#insight-5","date_modified":"2026-10-23"},{"text":"The land area required to produce food lost at the farm stage is estimated at 4.4 million km2, an area larger than the Indian sub-continent. Over half of this land use is associated with meat and animal products.","ai_generated":true,"unit":"wwf-000600#insight-6","date_modified":"2026-10-23"},{"text":"Freshwater withdrawals associated with global farm stage food losses are estimated at 760 km3. Cereals and pulses have the highest global water footprint, with specific hotspots in rice production in South and Southeast Asia and wheat production in North America and Asia.","ai_generated":true,"unit":"wwf-000600#insight-7","date_modified":"2026-10-23"},{"text":"Food loss drivers are categorized into direct factors (biological and environmental; agronomy, animal husbandry, and fishing practices; and technology and infrastructure) and indirect factors (market structure, governance, and investment; and human factors).","ai_generated":true,"unit":"wwf-000600#insight-8","date_modified":"2026-10-23"},{"text":"The report argues that the traditional distinction between 'food loss' (unintended) and 'food waste' (conscious decision) is misleading and does not help in identifying drivers or solutions.","ai_generated":true,"unit":"wwf-000600#insight-9","date_modified":"2026-10-23"},{"text":"Effective mitigation of farm stage food losses requires synchronized, holistic interventions rather than isolated technical fixes, combining technological improvements with training, better market connections, and fair pricing for farmers.","ai_generated":true,"unit":"wwf-000600#insight-10","date_modified":"2026-10-23"}],"climate_tags":["greenhouse gas emissions","land use","agricultural production","climate change","biodiversity loss"],"geography_discussed":["South and Southeast Asia","North America","Europe","India","United Kingdom","Pakistan","South Africa","Ghana","Benin","People's Republic of China","Peru","Trinidad and Tobago","Guyana","France","Ethiopia","Malawi","United States","Canada","Oceania","Lake Victoria"],"frame_perspective":[],"analysis_type":["quantitative assessment","environmental impact modeling","case study analysis"]},{"id":"wwf-001021","url":"https://climateinsightsdirectory.org/document/wwf-001021","title":"DEFORESTATION FRONTS DRIVERS AND RESPONSES IN A CHANGING WORLD","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"report","language":"en","date_published":"2021","source_url":"https://www.worldwildlife.org/documents/508/ocuoxmdil_Deforestation_fronts___drivers_and_responses_in_a_changing_world___f_3DJ6oVP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report identifies 24 deforestation fronts across Latin America, sub-Saharan Africa, Southeast Asia, and Oceania, where over 43 million hectares of forest were lost between 2004 and 2017. It argues that while commercial agriculture remains the dominant direct driver, indirect pressures such as population growth, dietary shifts toward meat, and weak governance amplify forest loss. The analysis evaluates a range of responses, from area-based protections and indigenous land rights to commodity-specific certifications and REDD+ frameworks, concluding that no single approach is sufficient and that integrated, context-specific solutions are required to halt deforestation.","ai_generated":true,"unit":"wwf-001021#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Between 2004 and 2017, 24 identified deforestation fronts lost over 43 million hectares of forest, an area approximately the size of Morocco.","ai_generated":true,"unit":"wwf-001021#insight-1","date_modified":"2026-10-23"},{"text":"Tropical and sub-tropical biomes were the primary sites of global forest loss, accounting for at least two-thirds of the total cover loss from 2000 to 2018.","ai_generated":true,"unit":"wwf-001021#insight-2","date_modified":"2026-10-23"},{"text":"Forest fragmentation is a widespread issue in these fronts, with nearly half (approximately 45%) of standing forests experiencing some form of fragmentation.","ai_generated":true,"unit":"wwf-001021#insight-3","date_modified":"2026-10-23"},{"text":"Commercial agricultural expansion is the most significant direct driver of deforestation globally, particularly in Asia and Latin America, while small-scale agriculture is the primary driver in Africa.","ai_generated":true,"unit":"wwf-001021#insight-4","date_modified":"2026-10-23"},{"text":"Indirect drivers such as population growth, urbanization, and a global increase in meat consumption place sustained pressure on tropical forests.","ai_generated":true,"unit":"wwf-001021#insight-5","date_modified":"2026-10-23"},{"text":"Area-based responses, including protected areas and the recognition of indigenous peoples and local communities (IPLC) tenure rights, are effective at reducing forest loss but often suffer from a lack of management capacity and financial resources.","ai_generated":true,"unit":"wwf-001021#insight-6","date_modified":"2026-10-23"},{"text":"Commodity-specific responses, such as voluntary certification and zero-deforestation commitments, have had limited impact at scale, often due to low uptake by upstream suppliers and difficulties in tracing smallholders.","ai_generated":true,"unit":"wwf-001021#insight-7","date_modified":"2026-10-23"},{"text":"The REDD+ mechanism has faced challenges in achieving its original goals due to complex negotiations and a lack of consistent results-based payments to forest-rich countries.","ai_generated":true,"unit":"wwf-001021#insight-8","date_modified":"2026-10-23"},{"text":"Jurisdictional and landscape approaches are viewed as promising for coordinating public-private partnerships to achieve low-carbon development at sub-national scales.","ai_generated":true,"unit":"wwf-001021#insight-9","date_modified":"2026-10-23"},{"text":"In the Brazilian Amazon, the Soy Moratorium successfully reduced soy-driven deforestation, but cattle ranching remains a primary driver, complicated by 'cattle laundering' from indirect suppliers.","ai_generated":true,"unit":"wwf-001021#insight-10","date_modified":"2026-10-23"},{"text":"In the Lower Mekong region, the expansion of cash crops like rubber and oil palm, often through economic land concessions (ELCs), is a major driver of forest loss.","ai_generated":true,"unit":"wwf-001021#insight-11","date_modified":"2026-10-23"},{"text":"In Eastern Australia, cattle ranching is the chief driver of forest loss, accounting for 75% of the total.","ai_generated":true,"unit":"wwf-001021#insight-12","date_modified":"2026-10-23"}],"climate_tags":["deforestation","forest degradation","carbon sink","Reducing emissions from deforestation and forest degradation","indigenous people","land tenure","mining","carbon dioxide emissions","nature-based solutions"],"geography_discussed":["Brazil","Colombia","Peru","Bolivia","Venezuela","Guyana","Paraguay","Argentina","Mexico","Guatemala","Liberia","Ivory Coast","Ghana","Cameroon","Gabon","Republic of the Congo","Democratic Republic of the Congo","Central African Republic","Angola","Zambia","Mozambique","Madagascar","Cambodia","Laos","Myanmar","Indonesia","Malaysia","Papua New Guinea","Australia"],"frame_perspective":[],"analysis_type":["comparative analysis","spatial analysis","policy review"]},{"id":"wwfza-000156","url":"https://climateinsightsdirectory.org/document/wwfza-000156","title":"MAKING A BUSINESS CASE FOR SUSTAINABLE DAIRY PRODUCTION","publisher":{"name":"WWF South Africa","organization":"wwf-south-africa"},"document_type":"report","language":"en","date_published":"2021","source_url":"https://wwfafrica.awsassets.panda.org/downloads/wwf_nedbank_dairy_business_case_report_v2.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report uses a case study of 62 South African pasture-based dairy farms to argue that sustainable management practices lead to higher gross margins and lower environmental impacts. Key findings indicate that optimizing milk production relative to cow size and land area, rather than maximizing production per cow, reduces carbon footprints and increases profitability. The study highlights a strong negative correlation between soil carbon and nitrogen fertiliser application, suggesting that healthy soils reduce the need for chemical inputs. Projections suggest that widespread adoption of these practices in the Eastern Cape and KwaZulu-Natal could reduce total carbon emissions by 10% and excess nitrogen by 27% over five years.","ai_generated":true,"unit":"wwfza-000156#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"There is a clear positive correlation between lower environmental impact and higher farm profitability, with higher gross margins associated with lower carbon footprints and more efficient nitrogen and phosphorous utilisation.","ai_generated":true,"unit":"wwfza-000156#insight-1","date_modified":"2026-10-23"},{"text":"To increase profitability and limit environmental impact, farmers should focus on optimising milk production (per hectare and per liveweight) rather than maximising production per cow.","ai_generated":true,"unit":"wwfza-000156#insight-2","date_modified":"2026-10-23"},{"text":"Healthy soils with optimal carbon levels are negatively correlated with nitrogen fertiliser application rates, as natural nutrient cycling reduces the need for chemical inputs.","ai_generated":true,"unit":"wwfza-000156#insight-3","date_modified":"2026-10-23"},{"text":"The case study farms generally exhibit lower environmental impacts than global averages; the low-impact group has a lower average carbon footprint than Oceania (1.31 kg CO2e/kg FPCM), while the global average in 2015 was 2.40 kg CO2e/kg FPCM.","ai_generated":true,"unit":"wwfza-000156#insight-4","date_modified":"2026-10-23"},{"text":"Farm-grown feed is a critical driver of sustainability; farms that produce more of their own feed tend to be more profitable, although drought years in the study period forced a higher reliance on bought feed.","ai_generated":true,"unit":"wwfza-000156#insight-5","date_modified":"2026-10-23"},{"text":"Geographic location, climate, and soil type do not act as absolute limits to sustainability, as rainfall did not significantly impact economic or environmental performance across the study groups.","ai_generated":true,"unit":"wwfza-000156#insight-6","date_modified":"2026-10-23"},{"text":"Extrapolating the case study results to all pasture-based dairy farms in the Eastern Cape and KwaZulu-Natal over five years could reduce total carbon emissions by 10%, excess nitrogen by 27%, and phosphorous excess by 19%.","ai_generated":true,"unit":"wwfza-000156#insight-7","date_modified":"2026-10-23"},{"text":"Increasing soil carbon levels by 0.2% across all farms in the Eastern Cape and KwaZulu-Natal could store approximately 15.75 million tons of CO2e over five years, potentially making pasture-based dairy farming carbon neutral.","ai_generated":true,"unit":"wwfza-000156#insight-8","date_modified":"2026-10-23"},{"text":"Key barriers to the adoption of sustainable practices include the misconception that productivity must be sacrificed for environmental friendliness, a lack of accurate information, and social pressure from peers.","ai_generated":true,"unit":"wwfza-000156#insight-9","date_modified":"2026-10-23"}],"climate_tags":["regenerative agriculture","carbon footprint","greenhouse gas emissions","carbon sequestration","carbon neutrality","sustainable agriculture","climate finance","water management"],"geography_discussed":["Western Cape","Oceania","North America","Western Europe","Eastern Europe"],"frame_perspective":[],"analysis_type":["case study","correlation analysis","economic assessment","environmental impact assessment"]},{"id":"ember-000206","url":"https://climateinsightsdirectory.org/document/ember-000206","title":"Asian Electricity Data Transparency","publisher":{"name":"Ember","organization":"ember"},"document_type":"report","language":"en","date_published":"2020-11-26","source_url":"https://ember-energy.org/app/uploads/2020/11/Asian-Data-Transparency-Report.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report evaluates electricity data transparency in Asia and Oceania, scoring countries based on criteria such as time granularity, fuel-type breakdowns, and ease of access. It finds significant disparities in data quality, with some countries like Australia and India providing high-granularity data, while others like Indonesia, Vietnam, and Singapore suffer from poor timeliness or limited disaggregation.","ai_generated":true,"unit":"ember-000206#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The report establishes a scoring system for data transparency based on eight criteria: real-time granularity, fuel-type generation breakdowns, sub-national data, unit-level data, capacity data, additional metrics (e.g., load factors), ease of access (free, English, downloadable), and the existence of a unified national platform.","ai_generated":true,"unit":"ember-000206#insight-1","date_modified":"2026-10-23"},{"text":"Australia and India are among the highest-scoring countries. Australia provides hourly real-time data via OpenNEM, though it lacks capacity or investment data. India provides daily data with breakdowns by utility, region, sector, and unit, though it lacks data on efficiency, investment, or load factors.","ai_generated":true,"unit":"ember-000206#insight-2","date_modified":"2026-10-23"},{"text":"China's data is rated as 'Insufficient' because it lacks real-time data, has a one-month lag for monthly data, and suffers from inconsistencies where monthly and annual data for thermal generation do not reconcile well.","ai_generated":true,"unit":"ember-000206#insight-3","date_modified":"2026-10-23"},{"text":"Several countries are rated as having 'Poor quality or no timely data available', including Indonesia, Vietnam, Malaysia, Singapore, Hong Kong, and Mongolia. For example, Indonesia's highest granularity is annual data with an eight-month lag, and Vietnam's data is described as 'hugely inconsistent'.","ai_generated":true,"unit":"ember-000206#insight-4","date_modified":"2026-10-23"},{"text":"Japan's data transparency is rated as 'Insufficient' due to poor dataset consistency between sources like Enecho and renewables-ei, and a lack of fuel-specific fossil data in the most timely reports.","ai_generated":true,"unit":"ember-000206#insight-5","date_modified":"2026-10-23"},{"text":"There is no single timely, region-wide electricity data source for Asia, forcing reliance on national sources or global datasets from the IEA, EIA, Global Energy Monitor, and IRENA, which often have lags or paywalls.","ai_generated":true,"unit":"ember-000206#insight-6","date_modified":"2026-10-23"}],"climate_tags":["electricity generation","coal power","renewable energy","wind power"],"geography_discussed":["People's Republic of China","India","Japan","South Korea","Indonesia","Australia","Taiwan","Vietnam","Thailand","Malaysia","Philippines","Bangladesh","New Zealand","Singapore","Hong Kong","Mongolia"],"frame_perspective":[],"analysis_type":["data quality assessment","comparative analysis"]},{"id":"fordecl-000071","url":"https://climateinsightsdirectory.org/document/fordecl-000071","title":"Goal 6 assessment","publisher":{"name":"Forest Declaration Assessment","organization":"forest-declaration-assessment"},"document_type":"report","language":"en","date_published":"2020-11","source_url":"https://forestdeclaration.org/wp-content/uploads/2021/08/2020NYDFGoal6.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report concludes that Goal 6 was met through the adoption of SDG 15, but highlights significant gaps in how forest conservation is measured and reported. It notes that indicators for SDG target 15.2 measure net rather than gross deforestation, failing to capture the extent of natural forest loss. Furthermore, the report warns that SDG targets 15.1 and 15.2 were set to expire in 2020 without adopted revisions. Reporting challenges persist at national levels, with many countries lacking the data and statistical systems needed to track progress, while corporate reporting on SDGs remains largely superficial.","ai_generated":true,"unit":"fordecl-000071#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Goal 6 of the New York Declaration on Forests has been achieved via the adoption of Sustainable Development Goal (SDG) 15.","ai_generated":true,"unit":"fordecl-000071#insight-1","date_modified":"2026-10-23"},{"text":"There is a critical discrepancy in the measurement of deforestation under SDG target 15.2; while the target aims to end gross deforestation, the actual indicators only track net deforestation, which obscures the loss of natural forests.","ai_generated":true,"unit":"fordecl-000071#insight-2","date_modified":"2026-10-23"},{"text":"SDG target 15.2 lacks quantifiable indicators to track progress regarding the reforestation, afforestation, and restoration of forests.","ai_generated":true,"unit":"fordecl-000071#insight-3","date_modified":"2026-10-23"},{"text":"SDG targets 15.1 and 15.2 were scheduled to expire at the end of 2020, and as of the 51st session of the Statistical Commission in 2020, no revisions to these targets had been adopted.","ai_generated":true,"unit":"fordecl-000071#insight-4","date_modified":"2026-10-23"},{"text":"Global reporting on SDG 15 is hindered by significant data gaps, as countries frequently fail to collect data for more than half of the SDG indicators and many targets lack quantifiable components.","ai_generated":true,"unit":"fordecl-000071#insight-5","date_modified":"2026-10-23"},{"text":"National reporting through Voluntary National Reviews (VNRs) often lacks concrete monitoring and evaluation processes, and some countries report a tension between economic growth driven by the forestry sector and declining forest areas.","ai_generated":true,"unit":"fordecl-000071#insight-6","date_modified":"2026-10-23"},{"text":"While 72 percent of over 1,000 surveyed companies mention SDGs in their reporting, only 14 percent mention specific SDG targets, indicating a need for more concrete evaluation targets in corporate reporting.","ai_generated":true,"unit":"fordecl-000071#insight-7","date_modified":"2026-10-23"}],"climate_tags":["forest conservation","forest restoration","afforestation","reforestation","Sustainable Development Goals","deforestation","climate finance","biodiversity loss"],"geography_discussed":["sub-Saharan Africa","Northern Africa and Western Asia","Central and Southern Asia","Eastern and South-Eastern Asia","Latin America and the Caribbean","Australia and New Zealand","Oceania","Europe and Northern America"],"frame_perspective":[],"analysis_type":["policy assessment","progress monitoring"]},{"id":"fordecl-000181","url":"https://climateinsightsdirectory.org/document/fordecl-000181","title":"GOAL ASSESSMENT PROGRESS ON THE NEW YORK DECLARATION ON FORESTS","publisher":{"name":"Forest Declaration Assessment","organization":"forest-declaration-assessment"},"document_type":"report","language":"en","date_published":"2020-11","source_url":"https://forestdeclaration.org/wp-content/uploads/2022/08/2020NYDFGoal1-low-res.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The 2020 Goal 1 assessment concludes that the world is failing to halve natural forest loss and associated greenhouse gas emissions by 2020 and is not on track to stop them by 2030. Using data from Global Forest Watch and the FAO, the report finds that global annual gross tree cover loss has increased by 40% since the NYDF was signed in 2014 compared to the 2001-2013 baseline. Humid tropical primary forest loss has increased by 41% on average since the baseline period. While net natural forest loss decreased slightly from 10.4 million hectares per year (2000-2010) to 7.8 million hectares per year (2010-2020), this is insufficient to meet targets. Tropical Africa is identified as an emerging frontier of forest loss, while Latin America remains the region with the highest absolute area of primary forest loss. Greenhouse gas emissions from deforestation and primary forest loss are also moving away from 2030 targets, with primary forest emissions 45% higher since the NYDF signing than before.","ai_generated":true,"unit":"fordecl-000181#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The world has failed to meet the 2020 target of halving forest loss and greenhouse gas emissions and is not on track to eliminate them by 2030. The required sustained reductions to meet the 2030 target are described as \"unprecedented and are highly unlikely.\"","ai_generated":true,"unit":"fordecl-000181#insight-1","date_modified":"2026-10-23"},{"text":"Global gross tree cover loss has increased significantly since the signing of the NYDF in 2014. The average annual loss between 2014 and 2019 was 40% higher than the 2001-2013 baseline, rising from 18 to 25 million hectares per year.","ai_generated":true,"unit":"fordecl-000181#insight-2","date_modified":"2026-10-23"},{"text":"Humid tropical primary forest loss has increased by an average of 41% since the baseline period, moving from 3.0 to 4.2 million hectares per year. To reach the 2030 target of zero loss, this must decrease by 340,000 hectares each year.","ai_generated":true,"unit":"fordecl-000181#insight-3","date_modified":"2026-10-23"},{"text":"Global net natural forest loss showed a slight decrease, falling from 10.4 million hectares per year (2000-2010) to 7.8 million hectares per year (2010-2020), but remains far above the 2020 target of 5.2 million hectares per year.","ai_generated":true,"unit":"fordecl-000181#insight-4","date_modified":"2026-10-23"},{"text":"Tropical Africa has emerged as a major frontier for forest loss, showing the largest relative increase in both tropical deforestation and primary forest loss compared to the baseline period.","ai_generated":true,"unit":"fordecl-000181#insight-5","date_modified":"2026-10-23"},{"text":"Latin America accounts for more than half of all annual tropical primary forest loss, with a loss of 2.34 million hectares per year between 2014 and 2019, the highest absolute area among tropical regions.","ai_generated":true,"unit":"fordecl-000181#insight-6","date_modified":"2026-10-23"},{"text":"Greenhouse gas emissions from forest loss are increasing. Gross emissions from humid tropical primary forest loss were 1.8 Gt CO2 in 2019, which is 62% above the 2020 target of 0.70 Gt CO2.","ai_generated":true,"unit":"fordecl-000181#insight-7","date_modified":"2026-10-23"}],"climate_tags":["deforestation","greenhouse gas emissions","carbon dioxide emissions","remote sensing","Paris Agreement","carbon capture and storage","biodiversity"],"geography_discussed":["Africa","Latin America","Asia","South America","Europe","Oceania","Brazil"],"frame_perspective":[],"analysis_type":["progress assessment","trend analysis"]},{"id":"iisd-002350","url":"https://climateinsightsdirectory.org/document/iisd-002350","title":"Supporting the Implementation of New WTO Rules on Fisheries Subsidies","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"policy brief","language":"en","date_published":"2020-11","source_url":"https://www.iisd.org/system/files/2020-12/wto-fisheries-subsidies-technical-assistance.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document identifies six key areas where technical assistance and capacity building (TACB) are needed to implement a future WTO instrument on fisheries subsidies: identifying and notifying subsidies, ensuring compliance with prohibitions, establishing domestic rules, re-purposing subsidy schemes, identifying IUU fishing and overfished stocks, and strengthening management regimes. Analysis of OECD and Pew Charitable Trusts data from 2012–2017 reveals that while fisheries-related official development assistance (ODA) has grown, it remains a small fraction (0.3%) of total sector-allocable ODA. The brief finds a significant gap in support for subsidy reform and IUU monitoring, while a large portion of funding is directed toward general fisheries management and development projects that may inadvertently increase fishing capacity in regions like Africa.","ai_generated":true,"unit":"iisd-002350#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Implementation of a future WTO instrument on fisheries subsidies will require members to undertake several compliance steps, including creating inventories of existing subsidies to meet notification requirements and establishing mechanisms to withdraw prohibited support, such as subsidies for vessel construction or fuel.","ai_generated":true,"unit":"iisd-002350#insight-1","date_modified":"2026-10-23"},{"text":"Beyond legal compliance, the effectiveness of a new WTO instrument depends on broader capacity building in areas such as re-purposing harmful subsidies toward social protection or sustainable management, improving the detection of illegal, unreported, and unregulated (IUU) fishing, and conducting regular fish stock assessments.","ai_generated":true,"unit":"iisd-002350#insight-2","date_modified":"2026-10-23"},{"text":"Official development assistance (ODA) for the fisheries sector between 2009 and 2018 totaled over USD 3.3 billion, but this represents only 0.3% of total sector-allocable ODA.","ai_generated":true,"unit":"iisd-002350#insight-3","date_modified":"2026-10-23"},{"text":"Analysis of ODA disbursements from 2012 to 2017 shows a critical lack of funding for subsidy reform and IUU monitoring; specifically, IUU monitoring and enforcement accounted for only 2% of total disbursements, and fish stock assessments and preservation accounted for only 1%.","ai_generated":true,"unit":"iisd-002350#insight-4","date_modified":"2026-10-23"},{"text":"A significant portion of fisheries-related ODA, particularly in Africa, is directed toward 'fisheries development' (such as building ports and providing engines), which may conflict with WTO goals by increasing fishing capacity and effort in areas with limited management capacity.","ai_generated":true,"unit":"iisd-002350#insight-5","date_modified":"2026-10-23"},{"text":"The document recommends that capacity-constrained members conduct country-specific needs assessments, potentially following the model of the WTO Trade Facilitation Agreement, to map gaps in their ability to implement new fisheries subsidy rules.","ai_generated":true,"unit":"iisd-002350#insight-6","date_modified":"2026-10-23"}],"climate_tags":["sustainable development","trade policy"],"geography_discussed":["Africa","Asia","Americas","Oceania","Europe","Morocco"],"frame_perspective":[],"analysis_type":["policy analysis","financial analysis"]},{"id":"sei-001035","url":"https://climateinsightsdirectory.org/document/sei-001035","title":"Improving WHO urban air pollutant database","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2020-04-25","source_url":"https://www.sei.org/publications/improving-who-urban-air-pollutant-database/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The paper evaluates the 2018 WHO global ambient air quality database, which contains PM10 and PM2.5 data for thousands of cities worldwide. It identifies challenges in comparing air pollution across different income levels and warns that the database has been used to draw inaccurate conclusions.","ai_generated":true,"unit":"sei-001035#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The 2018 WHO global ambient air quality database contains PM10 monitoring data for 3,570 cities across 97 countries and PM2.5 data for 2,628 cities in 81 countries, utilizing measurements and estimates from public monitoring systems.","ai_generated":true,"unit":"sei-001035#insight-1","date_modified":"2026-10-23"},{"text":"Urban particulate matter pollution levels are relatively low in high-income countries in Oceania, the Americas, the Western Pacific, and Western Europe, while high levels persist in low- and middle-income countries in Latin America, Southeast Asia, and Africa, where staffing and funding shortages hinder pollution reduction.","ai_generated":true,"unit":"sei-001035#insight-2","date_modified":"2026-10-23"},{"text":"The database has been used by the media, organizations, and politicians to reach misleading and inaccurate conclusions when making comparisons between cities, a problem that also occurred with the 2016 version.","ai_generated":true,"unit":"sei-001035#insight-3","date_modified":"2026-10-23"}],"climate_tags":["air pollution","particulates","public health"],"geography_discussed":["Western Europe","Americas","Western Pacific","Oceania","Africa","Southeast Asia","Latin America"],"frame_perspective":[],"analysis_type":["database evaluation"]},{"id":"wwf-000871","url":"https://climateinsightsdirectory.org/document/wwf-000871","title":"DEFORESTATION FRONTS DRIVERS AND RESPONSES IN A CHANGING WORLD","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"report","language":"en","date_published":"2020","source_url":"https://www.worldwildlife.org/documents/507/9bsfj8aq5v_deforestation_fronts___drivers_and_responses_in_a_changing_world____8p3if5q.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report identifies 24 'deforestation fronts' across Latin America, sub-Saharan Africa, Southeast Asia, and Oceania where over 43 million hectares of forest were lost between 2004 and 2017. It argues that while commercial agriculture, tree plantations, and extractive activities are primary drivers, responses must be tailored to local contexts and integrated across area-based and sector-specific approaches to be effective.","ai_generated":true,"unit":"wwf-000871#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Between 2004 and 2017, over 43 million hectares of forest were lost within 24 identified 'deforestation fronts', an area comparable in size to Morocco.","ai_generated":true,"unit":"wwf-000871#insight-1","date_modified":"2026-10-23"},{"text":"The 24 deforestation fronts cover 710 million hectares, of which half is forested; approximately 45% of the remaining forest in these areas has experienced fragmentation, increasing vulnerability to fire and human intervention.","ai_generated":true,"unit":"wwf-000871#insight-2","date_modified":"2026-10-23"},{"text":"Commercial agriculture and tree plantations are the primary global drivers of deforestation, though specific drivers vary by region: cattle ranching and soy dominate in Latin America, while timber and oil palm are primary in Southeast Asia.","ai_generated":true,"unit":"wwf-000871#insight-3","date_modified":"2026-10-23"},{"text":"In sub-Saharan Africa, subsistence agriculture is a key driver of forest loss, though commercial agriculture is expanding and small-scale timber extraction for energy contributes to forest degradation.","ai_generated":true,"unit":"wwf-000871#insight-4","date_modified":"2026-10-23"},{"text":"Area-based responses, such as protected areas and the recognition of indigenous peoples and local communities (IPLC) tenure rights, are effective at preventing loss within their boundaries but cannot prevent 'leakage' (the displacement of deforestation) to other areas.","ai_generated":true,"unit":"wwf-000871#insight-5","date_modified":"2026-10-23"},{"text":"Sector-specific responses, including voluntary certification and zero-deforestation supply chains, have had limited impact at scale and often struggle without supportive national laws and policies.","ai_generated":true,"unit":"wwf-000871#insight-6","date_modified":"2026-10-23"},{"text":"Integrated approaches, such as REDD+ and jurisdictional or landscape-based partnerships, aim to combine multiple interventions to achieve sustainable development and low-carbon economies at sub-national scales.","ai_generated":true,"unit":"wwf-000871#insight-7","date_modified":"2026-10-23"}],"climate_tags":["deforestation","forest degradation","carbon sink","biodiversity","Reducing emissions from deforestation and forest degradation"],"geography_discussed":["Latin America","sub-Saharan Africa","Southeast Asia","Oceania","Brazil","Colombia","Peru","Bolivia","Venezuela","Guyana","Paraguay","Argentina","Ecuador","Mexico","Guatemala","Liberia","Ivory Coast","Ghana","Cameroon","Gabon","Republic of the Congo","Democratic Republic of the Congo","Central African Republic","Angola","Zambia","Mozambique","Madagascar","Cambodia","Laos","Myanmar","Indonesia","Malaysia","Papua New Guinea","Australia","Morocco"],"frame_perspective":[],"analysis_type":["driver analysis","policy evaluation"]}]}