{"query_echo":{"q":"","filters":{"analysis_type":["quantitative analysis"]},"warnings":[]},"total":{"value":472,"relation":"eq"},"page":14,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=quantitative+analysis&page=14","next":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=quantitative+analysis&page=15","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":"seforall-000190","url":"https://climateinsightsdirectory.org/document/seforall-000190","title":"CHILLING PROSPECTS: TRACKING SUSTAINABLE COOLING FOR ALL 2019","publisher":{"name":"Sustainable Energy for All","organization":"sustainable-energy-for-all"},"document_type":"fact sheet","language":"en","date_published":"2019","source_url":"https://www.seforall.org/system/files/2019-11/SEforALL-Chilling_Prospects-Infographic.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document reports that 1.05 billion people remained at the highest risk of cooling insecurity in 2019, down from 1.1 billion in 2018. It identifies the 'Critical 9' countries with the largest populations at high risk, including India, China, and Nigeria, and notes that China and India have already developed National Cooling Plans, while Brazil, Nigeria, and Bangladesh are currently developing them.","ai_generated":true,"unit":"seforall-000190#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"In 2019, 1.05 billion people remained at the highest risk of cooling insecurity, a decrease from 1.1 billion in 2018. This high-risk group consists of the Rural Poor (365 million) and Urban Poor (680 million).","ai_generated":true,"unit":"seforall-000190#insight-1","date_modified":"2026-10-23"},{"text":"Twelve African countries have over 60% of their populations at high risk (Rural and Urban Poor): Angola, Benin, Burkina Faso, Djibuti, Guinea-Bissau, Liberia, Malawi, Mali, Mozambique, Nigeria, South Sudan, and Togo.","ai_generated":true,"unit":"seforall-000190#insight-2","date_modified":"2026-10-23"},{"text":"The 'Critical 9' countries with the largest number of people at high risk are India, China, Indonesia, Pakistan, Bangladesh, Nigeria, Mozambique, Sudan, and Brazil. China and India have developed National Cooling Plans, while Brazil, Nigeria, and Bangladesh are in the process of developing them.","ai_generated":true,"unit":"seforall-000190#insight-3","date_modified":"2026-10-23"}],"climate_tags":["energy access","greenhouse gas emissions","energy efficiency"],"geography_discussed":["Africa","Asia","Angola","Benin","Burkina Faso","Djibouti","Guinea-Bissau","Liberia","Malawi","Mali","Mozambique","Nigeria","South Sudan","Togo","India","People's Republic of China","Indonesia","Pakistan","Bangladesh","Sudan","Brazil"],"frame_perspective":[],"analysis_type":["quantitative analysis","trend analysis"]},{"id":"sei-001127","url":"https://climateinsightsdirectory.org/document/sei-001127","title":"Konsumtionsbaserade utsläpp i Umeå kommun","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"report","language":"sv","date_published":"2018-12","source_url":"https://www.sei.org/wp-content/uploads/2019/06/2019-sei-report-umea-konsumtionbaserad-utslapp.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes the consumption-based greenhouse gas emissions of Umeå residents, finding an average footprint of 9.77 tonnes CO2e per person for survey participants (aged 20-84), which scales to 7.6 tonnes CO2e per person for the total population. Travel, particularly aviation and car use, is identified as the primary emission source, followed by food. The report identifies 'hotspots' including meat consumption, aviation, and housing energy, and recommends administrative, economic, and informative policy tools to reduce these impacts.","ai_generated":true,"unit":"sei-001127#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Travel is the largest contributor to the climate footprint among respondents, generating 4.7 tonnes CO2e per person, with aviation accounting for 3.05 tonnes and car travel for 1.52 tonnes.","ai_generated":true,"unit":"sei-001127#insight-1","date_modified":"2026-10-23"},{"text":"Food consumption is the second largest source of emissions at 2.5 tonnes CO2e per person, which is approximately 10% higher than the Swedish national average of 2.1 tonnes.","ai_generated":true,"unit":"sei-001127#insight-2","date_modified":"2026-10-23"},{"text":"Climate impact varies by age and gender; the lowest footprint is found among men aged 20-29 (9.15 tonnes CO2e), while the highest is among men aged 50-64 (11.06 tonnes CO2e).","ai_generated":true,"unit":"sei-001127#insight-3","date_modified":"2026-10-23"},{"text":"The report identifies specific 'hotspots' for emission reductions: aviation and car use in travel; meat consumption, dairy products, and food waste in food; housing energy in housing; and clothing and furniture in gadgets.","ai_generated":true,"unit":"sei-001127#insight-4","date_modified":"2026-10-23"},{"text":"Umeå residents fly significantly more than the Swedish average, with private domestic flights averaging 2.3 trips per year and private European flights 1.4 trips per year.","ai_generated":true,"unit":"sei-001127#insight-5","date_modified":"2026-10-23"},{"text":"Regarding housing energy, 50% of respondents use district heating, 23% use heat pumps, and 8.6% use direct-acting electricity; only 18% have origin-marked or environmentally marked electricity.","ai_generated":true,"unit":"sei-001127#insight-6","date_modified":"2026-10-23"},{"text":"The report suggests various policy tools for the municipality, including administrative measures (urban densification via the comprehensive plan), economic measures (differentiated waste taxes for food waste), and informative measures (integrating climate impact into school curricula).","ai_generated":true,"unit":"sei-001127#insight-7","date_modified":"2026-10-23"}],"climate_tags":["carbon footprint","aviation","road transport","food waste","district heating","heat pump","renewable electricity","urban planning","sustainable consumption"],"geography_discussed":["Sweden"],"frame_perspective":[],"analysis_type":["quantitative analysis","comparative analysis","policy recommendation"]},{"id":"sei-000794","url":"https://climateinsightsdirectory.org/document/sei-000794","title":"Closing the global ozone yield gap: quantification, co-benefits and multi-stress tolerance","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2018-08-07","source_url":"https://www.sei.org/publications/closing-global-ozone-yield-gap-quantification-cobenefits-multistress-tolerance/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study estimates that tropospheric ozone significantly reduces global yields for soybean, wheat, rice, and maize, with the highest losses occurring in regions already stressed by pests, heat, and nutrient deficiencies. It advocates for integrating ozone tolerance into crop breeding programmes and altering management approaches to close the 'ozone yield gap'.","ai_generated":true,"unit":"sei-000794#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Tropospheric ozone (based on 2010–2012 means) causes significant annual global yield reductions across four major crops, totaling 227 Tg of lost yield. The impact varies by crop, with soybean being the most sensitive and maize the least.","ai_generated":true,"unit":"sei-000794#insight-1","date_modified":"2026-10-23"},{"text":"The highest ozone-induced production losses are geographically concentrated: soybean losses are highest in North and South America; wheat in India and China; rice in parts of India, Bangladesh, China, and Indonesia; and maize in China and the United States.","ai_generated":true,"unit":"sei-000794#insight-2","date_modified":"2026-10-23"},{"text":"Regions suffering high ozone-induced crop losses frequently overlap with areas vulnerable to other abiotic and biotic stresses, including heat stress, pests, diseases, aridity, and nutrient stress.","ai_generated":true,"unit":"sei-000794#insight-3","date_modified":"2026-10-23"}],"climate_tags":["crop yield","food security"],"geography_discussed":["North America","South America","India","People's Republic of China","Bangladesh","Indonesia","United States"],"frame_perspective":[],"analysis_type":["quantitative analysis","modelling"]},{"id":"wwf-000544","url":"https://climateinsightsdirectory.org/document/wwf-000544","title":"MAXIMIZING FARM RESOURCES AND EDIBLE FOOD RESCUE Specialty Crop Loss Report","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"report","language":"en","date_published":"2018-08","source_url":"https://www.worldwildlife.org/documents/1165/50prkclal9_WWF_Farm_Loss_Technical_Report_Redacted_0619.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes food loss in fresh tomatoes, peaches, processing potatoes, and romaine lettuce across several US states. It finds that loss rates vary significantly by crop, with romaine lettuce seeing the highest losses (average 56%) and processing potatoes the lowest (average 2.6%). Key drivers of loss include strict cosmetic standards, market price fluctuations, and labor shortages. While most lost produce is tilled back into the soil or used for animal feed, the report argues that creating secondary markets and improving information flows could reduce this waste and address food insecurity.","ai_generated":true,"unit":"wwf-000544#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Romaine lettuce exhibits the highest in-field loss among the studied crops, with a calculated average loss of 56% (approximately 417 million pounds), largely due to the trimming of outer leaves to produce hearts and heads.","ai_generated":true,"unit":"wwf-000544#insight-1","date_modified":"2026-10-23"},{"text":"Processing potatoes are the most efficient of the studied crops, with a measured in-field loss of only 2% and a transloading site loss rate averaging 2.6%.","ai_generated":true,"unit":"wwf-000544#insight-2","date_modified":"2026-10-23"},{"text":"Fresh market tomatoes in Florida showed an average measured in-field loss of 40% and an average packinghouse loss of 39%, with 39% of in-field culls having no visible quality problems.","ai_generated":true,"unit":"wwf-000544#insight-3","date_modified":"2026-10-23"},{"text":"Fresh market peaches in New Jersey had an average measured in-field loss of 37% and a packinghouse loss of approximately 14%.","ai_generated":true,"unit":"wwf-000544#insight-4","date_modified":"2026-10-23"},{"text":"The primary drivers of food loss are market dynamics and strict cosmetic standards; produce is often left in the field if it is too small, misshapen, or if the market price falls below the cost of harvesting and labor.","ai_generated":true,"unit":"wwf-000544#insight-5","date_modified":"2026-10-23"},{"text":"Most on-farm food loss is not sent to landfills but is instead tilled back into the soil, used as animal feed, or left to decompose, meaning growers often do not view it as 'waste'.","ai_generated":true,"unit":"wwf-000544#insight-6","date_modified":"2026-10-23"},{"text":"Food recovery efforts, such as gleaning, are hindered by the Food Safety Modernization Act (FSMA), which limits the ability of untrained persons to enter fields, as well as grower concerns regarding liability and operational disruption.","ai_generated":true,"unit":"wwf-000544#insight-7","date_modified":"2026-10-23"},{"text":"Life-cycle assessments indicate that the environmental burdens of processed peach production are higher than the other annual crops studied, with diesel use and N-based fertilizers being top contributors to impact.","ai_generated":true,"unit":"wwf-000544#insight-8","date_modified":"2026-10-23"}],"climate_tags":["greenhouse gas emissions","life cycle assessment","biodiversity loss","soil erosion"],"geography_discussed":["Florida","New Jersey","Idaho","Arizona","California"],"frame_perspective":[],"analysis_type":["quantitative analysis","qualitative analysis","life-cycle assessment"]},{"id":"prio-001860","url":"https://climateinsightsdirectory.org/document/prio-001860","title":"Who Revolts? Empirically Revisiting the Social Origins of Democracy","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":"2018-07-19","source_url":"https://cdn.cloud.prio.org/files/f06b30aa-4a58-4b2f-89da-7c74ec641b53/Who Revolts Empirically Revisiting the Social Origins of Democracy.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The research argues that democratization is more likely when opposition movements are led by urban groups—industrial workers and the middle class—who possess both the motivation to seek democratic policies and the organizational capacity to challenge regimes. Using a dataset of 193 campaigns across 147 countries, the authors find that movements dominated by industrial workers have a robust and significant positive effect on democratization. In contrast, movements dominated by peasants or military personnel are not conducive to democratization, and the evidence for middle-class-led campaigns is mixed, appearing more effective when limited to students and educated professionals or non-violent tactics.","ai_generated":true,"unit":"prio-001860#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Opposition movements dominated by urban groups, specifically industrial workers or the urban middle classes, are more likely to result in democracy than movements led by other groups or situations where no organized mass opposition exists.","ai_generated":true,"unit":"prio-001860#insight-1","date_modified":"2026-10-23"},{"text":"The positive relationship between urban-led campaigns and democratization is more pronounced in societies with higher levels of urbanization and in more recent decades.","ai_generated":true,"unit":"prio-001860#insight-2","date_modified":"2026-10-23"},{"text":"Among urban groups, campaigns dominated by industrial workers show a very robust and statistically significant link to democratization, whereas the evidence for middle-class-led campaigns is less consistent.","ai_generated":true,"unit":"prio-001860#insight-3","date_modified":"2026-10-23"},{"text":"Movements dominated by peasants or military personnel do not promote democratization and may even be followed by democratic backsliding.","ai_generated":true,"unit":"prio-001860#insight-4","date_modified":"2026-10-23"},{"text":"The authors posit that industrial workers are key agents of democratization because they combine the motivation for redistributive policies with high organizational capacity through unions and labor parties, and strategic leverage via strikes in vital economic sectors.","ai_generated":true,"unit":"prio-001860#insight-5","date_modified":"2026-10-23"},{"text":"Further analysis suggests that the democratizing effect of the middle class may be driven specifically by sub-groups such as students and educated professionals, and may depend on the use of non-violent tactics.","ai_generated":true,"unit":"prio-001860#insight-6","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Ukraine"],"frame_perspective":[],"analysis_type":["quantitative analysis","cross-sectional time-series analysis","comparative political sociology"]},{"id":"cdkn-000702","url":"https://climateinsightsdirectory.org/document/cdkn-000702","title":"Hacia la resiliencia hídrica en paisajes urbano-amazónicos: Estrategias para Tarapoto y la microcuenca del Río Cumbaza (Perú)","publisher":{"name":"Climate and Development Knowledge Network","organization":"climate-and-development-knowledge-network"},"document_type":"policy brief","language":"es","date_published":"2018-05","source_url":"https://cdkn.org/sites/default/files/files/Nexus-in-Tarapato-Peru_policy-brief.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document analyzes the critical link between forest cover and water security in the Cumbaza River micro-basin, noting that 85% of the area is degraded. It highlights how deforestation and climate variability increase sediment loads, affecting urban water treatment for 40,000 users in Tarapoto and reducing water availability for rice and aquaculture farmers. The brief recommends restoring 3,000 hectares in the upper basin by 2040 and 1,500 hectares in the Ahuashiyacu and Shilcayo sub-basins by 2050, while strengthening inter-institutional governance through the Cumbaza Micro-basin Management Committee.","ai_generated":true,"unit":"cdkn-000702#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Environmental degradation and climate change are compromising water security in the Cumbaza River micro-basin through precipitation variability and peak flow changes.","ai_generated":true,"unit":"cdkn-000702#insight-1","date_modified":"2026-10-23"},{"text":"Significant deforestation has occurred in the micro-basin, with 58% of forest cover lost between 1977 and 2005, and an estimated 85% of the total 57,120-hectare surface currently degraded.","ai_generated":true,"unit":"cdkn-000702#insight-2","date_modified":"2026-10-23"},{"text":"Increased sediment loads in the Shilcayo, Cachiyacu, and Ahuashiyacu rivers—driven by land-use change and climate extremes—hinder the water treatment operations of EMAPA San Martín, impacting 40,000 urban users in Tarapoto.","ai_generated":true,"unit":"cdkn-000702#insight-3","date_modified":"2026-10-23"},{"text":"The agricultural sector, particularly rice and aquaculture, faces water scarcity during the dry season (May to September) due to a historical trend of reducing annual flows in the Cumbaza River and a 50% loss in the irrigation canal system.","ai_generated":true,"unit":"cdkn-000702#insight-4","date_modified":"2026-10-23"},{"text":"Future projections for 2050 indicate that agricultural water demand for the Cumbaza River could reach 151 million m3/year, double the current consumption, necessitating a transition to mixed agro-aquacultural systems.","ai_generated":true,"unit":"cdkn-000702#insight-5","date_modified":"2026-10-23"},{"text":"To ensure base flows and sediment retention, the report recommends recovering 3,000 hectares in the upper micro-basin by 2040 and at least 20% (approximately 1,500 hectares) of degraded areas in the Ahuashiyacu and Shilcayo sub-basins by 2050.","ai_generated":true,"unit":"cdkn-000702#insight-6","date_modified":"2026-10-23"},{"text":"Effective water governance requires strengthening multi-actor platforms, specifically the Cumbaza Micro-basin Management Committee (CGMC), to coordinate funding, avoid duplication of interventions, and integrate monitoring systems.","ai_generated":true,"unit":"cdkn-000702#insight-7","date_modified":"2026-10-23"}],"climate_tags":["water security","deforestation","climate change","green infrastructure","agroforestry","agricultural irrigation","aquaculture","water-management"],"geography_discussed":["San Martín","Cordillera Escalera Regional Conservation Area"],"frame_perspective":[],"analysis_type":["scenario analysis","qualitative analysis","quantitative analysis"]},{"id":"clibonds-001027","url":"https://climateinsightsdirectory.org/document/clibonds-001027","title":"Green Bond Pricing in the Primary Market: October - December 2017","publisher":{"name":"Climate Bonds Initiative","organization":"climate-bonds-initiative"},"document_type":"report","language":"en","date_published":"2018-05","source_url":"https://www.climatebonds.net/files/drupal-files/files/Greenium_Q4-07B.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report analyzes 23 green bonds totaling USD 15.1bn issued in Q4 2017. It finds that USD green bonds generally achieve higher oversubscription and tighter pricing relative to initial price thoughts than vanilla bonds, while EUR green bonds perform similarly. Approximately 44% of allocations went to green investors. The 'greenium' (pricing inside the yield curve) was observed in only half of a limited sample of six bonds, indicating that a new issue premium is not always avoided. In the secondary market, over half of EUR green bonds outperformed their indices after 28 days, whereas USD green bonds lagged.","ai_generated":true,"unit":"clibonds-001027#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"USD green bonds demonstrated stronger primary market demand than vanilla equivalents in Q4 2017, achieving higher average oversubscription (2.7x vs 2.2x) and tighter pricing relative to Initial Price Thoughts (IPT).","ai_generated":true,"unit":"clibonds-001027#insight-1","date_modified":"2026-10-23"},{"text":"EUR green bonds showed performance similar to vanilla bonds in the primary market, with an average oversubscription of 2.9x compared to 3x for vanilla bonds, and final pricing averaging 11bps tighter than IPT versus 13bps for vanilla.","ai_generated":true,"unit":"clibonds-001027#insight-2","date_modified":"2026-10-23"},{"text":"Investor allocation for green bonds in the sample averaged 44% for those identifying as green or socially responsible investors, representing a slight decline from 47% in Q3 2017.","ai_generated":true,"unit":"clibonds-001027#insight-3","date_modified":"2026-10-23"},{"text":"The existence of a 'greenium' (where a bond is issued at a lower yield than existing debt) is inconsistent; in a sample of six bonds, three exhibited a greenium and three exhibited a traditional new issue premium.","ai_generated":true,"unit":"clibonds-001027#insight-4","date_modified":"2026-10-23"},{"text":"In the immediate secondary market, EUR green bonds generally outperformed their indices, with 66% tightening more than their corresponding index after 28 days, while only 25% of USD green bonds did the same.","ai_generated":true,"unit":"clibonds-001027#insight-5","date_modified":"2026-10-23"},{"text":"While 14 of 22 issuers in the sample were first-time green bond issuers, the market lacks sector diversity, as all bonds originated from the financial, real estate, and utility sectors.","ai_generated":true,"unit":"clibonds-001027#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate bond","climate finance","sustainable finance"],"geography_discussed":["Japan","Denmark","Germany","Italy","Spain","People's Republic of China","India","United States"],"frame_perspective":[],"analysis_type":["quantitative analysis","comparative study"]},{"id":"sei-000292","url":"https://climateinsightsdirectory.org/document/sei-000292","title":"Analysis of distributions of hourly NO2 concentrations contributing to annual average NO2 concentrations across the European monitoring network 2000-2014","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2018-03-12","source_url":"https://www.sei.org/publications/analysis-distributions-hourly-no2-concentrations-contributing-annual-average-no2-concentrations-across-european-monitoring-network-2000-2014/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The analysis of over 2,500 European monitoring sites reveals that annual average NO2 concentrations are driven by diverse hourly and monthly contributions that do not follow specific regional patterns. Between 2000 and 2014, trends showed an increase in NO2 contributions from winter months and rush-hour periods, while the contribution from peak hourly concentrations decreased. Because sites with similar annual averages can have very different underlying concentration patterns due to local emissions, chemistry, and meteorology, the study argues that air quality mitigation strategies must be tailored to the specific variability of each location rather than applied uniformly.","ai_generated":true,"unit":"sei-000292#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Between 2010 and 2014, annual average NO2 concentrations exceeded the European Union limit value of 40µgm−3 at 8% of the more than 2,500 monitoring sites analyzed.","ai_generated":true,"unit":"sei-000292#insight-1","date_modified":"2026-10-23"},{"text":"Analysis of 259 sites between 2000 and 2014 indicates that the annual average NO2 concentration is increasingly influenced by winter months and rush-hour periods, while the influence of peak hourly concentrations has declined.","ai_generated":true,"unit":"sei-000292#insight-2","date_modified":"2026-10-23"},{"text":"The drivers of annual NO2 concentrations vary significantly even within small geographic areas, meaning that air quality reduction measures effective in one location may not work in another.","ai_generated":true,"unit":"sei-000292#insight-3","date_modified":"2026-10-23"}],"climate_tags":["air quality"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["quantitative analysis","trend analysis"]},{"id":"ucs-000237","url":"https://climateinsightsdirectory.org/document/ucs-000237","title":"Abandoning Science Advice","publisher":{"name":"Union of Concerned Scientists","organization":"union-of-concerned-scientists"},"document_type":"report","language":"en","date_published":"2018-01","source_url":"https://www.ucs.org/sites/default/files/attach/2018/01/abandoning-science-advice-appendix-b-detailed-results.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document presents a series of tables detailing the activity and composition of science advisory committees across six federal agencies (CDC, DOI, DOE, DOC, EPA, and FDA) from 1997 to 2017. It tracks the number of meetings held and the number of members for each committee, highlighting instances where committees failed to meet their charter requirements. Additionally, it lists the appointment status of 83 key science and technology positions under the Trump administration as of January 15, 2018, noting numerous vacancies in roles requiring Senate confirmation.","ai_generated":true,"unit":"ucs-000237#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The document tracks the meeting frequency of science advisory committees across six federal agencies from 1997 to 2017, including the Centers for Disease Control and Prevention, Department of Interior, Department of Energy, Department of Commerce, Environmental Protection Agency, and Food and Drug Administration.","ai_generated":true,"unit":"ucs-000237#insight-1","date_modified":"2026-10-23"},{"text":"Data for the Department of Interior's Advisory Committee on Climate Change and Natural Resource Science shows it held 1 meeting in 2014, 3 in 2015, 2 in 2016, and 1 in 2017, with membership dropping from 25 in 2014 to null in 2017.","ai_generated":true,"unit":"ucs-000237#insight-2","date_modified":"2026-10-23"},{"text":"The Environmental Protection Agency's Clean Air Scientific Advisory Committee saw its membership drop to 0 in 2017, compared to 8 members in 2016 and 7 members in the years 2004 through 2015.","ai_generated":true,"unit":"ucs-000237#insight-3","date_modified":"2026-10-23"},{"text":"As of January 15, 2018, many of the 83 key science and technology positions designated by the National Academy of Sciences remained unfilled under the Trump administration, particularly those requiring Senate confirmation.","ai_generated":true,"unit":"ucs-000237#insight-4","date_modified":"2026-10-23"},{"text":"Specific vacancies in key science roles as of January 2018 included the Director of the Office of Science and Technology Policy (OSTP), the Director of the US Geological Survey, and the Assistant Secretary for Energy Efficiency and Renewable Energy.","ai_generated":true,"unit":"ucs-000237#insight-5","date_modified":"2026-10-23"},{"text":"The report identifies a significant number of unfilled positions on the President's Council of Advisors on Science and Technology (PCAST), estimated at 20 based on the Obama administration's iteration.","ai_generated":true,"unit":"ucs-000237#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate change","environmental regulation","renewable energy"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["quantitative analysis","administrative audit"]},{"id":"cdkn-000792","url":"https://climateinsightsdirectory.org/document/cdkn-000792","title":"STRENGTHENING CLIMATE RESILIENCE IN URBAN AMAZONIA","publisher":{"name":"Climate and Development Knowledge Network","organization":"climate-and-development-knowledge-network"},"document_type":"case study","language":"en","date_published":"2018","source_url":"https://cdkn.org/sites/default/files/files/StrengtheningClimateResilienceCumbaza.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document applies a Water-Energy-Food (WEF) nexus approach to analyze the Cumbaza watershed in Peru, highlighting how deforestation and climate change threaten urban and rural resource security. It quantifies 11 key WEF interactions and projects resource demands through 2050, emphasizing the critical role of forest ecosystem services in maintaining water quality and quantity for the region's growing population.","ai_generated":true,"unit":"cdkn-000792#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The Cumbaza watershed experienced a significant loss of forest cover, with 58% lost between 1977 and 2005, leaving approximately 8,500 hectares or 15% of the watershed as forest.","ai_generated":true,"unit":"cdkn-000792#insight-1","date_modified":"2026-10-23"},{"text":"Deforestation in the upper watershed has led to increased erosion and sedimentation in rivers, which negatively impacts the water treatment capacity and increases costs for urban water services provided by EMAPA, particularly in the Shilcayo and Ayashiyacu sub-basins.","ai_generated":true,"unit":"cdkn-000792#insight-2","date_modified":"2026-10-23"},{"text":"The region is highly dependent on external food and energy sources; food imports constitute 47% of total consumption, and the fossil fuel energy required to transport these imports accounts for over 90% of the watershed's total energy demands.","ai_generated":true,"unit":"cdkn-000792#insight-3","date_modified":"2026-10-23"},{"text":"Future projections for 2050 under a business-as-usual scenario predict that the population will reach 335,000, leading to a 75% increase in food demand and a 61% increase in energy required for transportation and agricultural production.","ai_generated":true,"unit":"cdkn-000792#insight-4","date_modified":"2026-10-23"},{"text":"Forests are vital for the livelihoods of indigenous Kichwa-Lamas communities, providing drinking water, non-timber forest products, and fuelwood, which is used for food preparation by 94% of rural households compared to 23% of urban households.","ai_generated":true,"unit":"cdkn-000792#insight-5","date_modified":"2026-10-23"}],"climate_tags":["climate resilience","deforestation","water security","food security","energy security","urbanization","agroforestry","green infrastructure"],"geography_discussed":["Lamas","Lima","Chiclayo","Yurimaguas","Moyobamba","Tocache"],"frame_perspective":[],"analysis_type":["case study","quantitative analysis","qualitative analysis","scenario modeling"]},{"id":"fordecl-000054","url":"https://climateinsightsdirectory.org/document/fordecl-000054","title":"2018 Progress Assessment Goal 5 Update","publisher":{"name":"Forest Declaration Assessment","organization":"forest-declaration-assessment"},"document_type":"report","language":"en","date_published":"2018","source_url":"https://forestdeclaration.org/wp-content/uploads/2020/11/2018Goal5.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The 2018 Progress Assessment for Goal 5 indicates that Bonn Challenge pledges have reached 168.9 million hectares, surpassing the 2020 milestone in terms of pledges. However, actual implementation remains difficult to aggregate, with a five-country sample showing 13.4 million hectares under restoration. Analysis of Nationally Determined Contributions (NDCs) reveals that while 127 of 165 NDCs include forest landscape restoration (FLR) commitments, only 30% are quantifiable. When combining official NDC targets with non-target ambitions, 114 million hectares are reflected, representing one third of the 2030 target.","ai_generated":true,"unit":"fordecl-000054#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Bonn Challenge pledges have increased to 168.9 million hectares, with 94 million hectares pledged for 2020 and 74.6 million hectares for 2030, meaning the 150 million hectare milestone for 2020 has been surpassed in pledges.","ai_generated":true,"unit":"fordecl-000054#insight-1","date_modified":"2026-10-23"},{"text":"Measuring actual implementation is challenging, but a sample of five jurisdictions indicates that approximately 13.4 million hectares are currently under restoration, which is 41 percent of their combined pledges.","ai_generated":true,"unit":"fordecl-000054#insight-2","date_modified":"2026-10-23"},{"text":"Specific national progress reported includes Rwanda bringing 900,000 hectares into restoration since 2011, the United States conducting restoration across 12.3 million hectares between 2011 and 2016, and India reporting approximately 9.8 million hectares of restored degraded land.","ai_generated":true,"unit":"fordecl-000054#insight-3","date_modified":"2026-10-23"},{"text":"Of 165 Nationally Determined Contributions (NDCs), 127 contain forest landscape restoration (FLR) commitments, but only 30 percent of these make quantifiable mitigation or adaptation commitments, totaling 57 million hectares.","ai_generated":true,"unit":"fordecl-000054#insight-4","date_modified":"2026-10-23"},{"text":"Within the quantified NDC commitments, 25 million hectares from developing countries are unconditional, while 32 million hectares require international donor support.","ai_generated":true,"unit":"fordecl-000054#insight-5","date_modified":"2026-10-23"},{"text":"Non-target ambitions in NDCs—such as voluntary efforts or intended measures—add another 57 million hectares, bringing the total reflected in NDCs to 114 million hectares, or one third of the 2030 Goal 5 target.","ai_generated":true,"unit":"fordecl-000054#insight-6","date_modified":"2026-10-23"},{"text":"The Bonn Challenge Barometer of Progress, launched by the IUCN and the German government in 2016, provides a framework to track 'success factors' (policies, finance, and data) and 'results and benefits' (hectares restored, biodiversity, and carbon sequestration).","ai_generated":true,"unit":"fordecl-000054#insight-7","date_modified":"2026-10-23"},{"text":"FLR activities in NDCs are heavily skewed toward reforestation, with 98 percent of the 3.3 gigatons of CO2 equivalent in commitments expected to be achieved through reforestation rather than other forest management forms.","ai_generated":true,"unit":"fordecl-000054#insight-8","date_modified":"2026-10-23"}],"climate_tags":["Nationally Determined Contributions","climate change mitigation","climate change adaptation","reforestation","agroforestry","carbon sequestration","nature-based solutions","Mangrove restoration"],"geography_discussed":["Brazil","El Salvador","Mexico","Rwanda","United States","India","Germany"],"frame_perspective":[],"analysis_type":["progress assessment","quantitative analysis"]},{"id":"iisd-002604","url":"https://climateinsightsdirectory.org/document/iisd-002604","title":"The Potential for Carbon Dioxide Equivalent Sequestration in Agro-Manitoba","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"report","language":"en","date_published":"2017-12","source_url":"https://www.iisd.org/system/files/publications/carbon-dioxide-equivalent-sequestration-agro-manitoba.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report estimates that Agro-Manitoba has the potential to sequester between 1.3 and 3 megatonnes of CO2e per year. It evaluates six practices: wetlands, forestry, riparian buffers, minimum tillage, perennials, and cover crops, using both a maximum one-year snapshot and a 30-year cumulative approach. The analysis highlights that while cover crops and wetlands offer the highest sequestration potential, forestry and riparian buffers provide significant rates despite smaller land areas. The findings are aligned with the province's Growing Outcomes in Watersheds (GROW) program, suggesting a strong policy basis for incentivizing these practices to offset emissions from Manitoba's agricultural sector.","ai_generated":true,"unit":"iisd-002604#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The total annual CO2e sequestration potential for Agro-Manitoba is estimated to range from 1,334,636 tCO2e (low scenario) to 1,707,978 tCO2e (high scenario) when averaged over 30 years.","ai_generated":true,"unit":"iisd-002604#insight-1","date_modified":"2026-10-23"},{"text":"Under a maximum one-year approach, the total sequestration potential ranges from 2,441,825 to 3,072,825 tCO2e, with cover crops and wetlands identified as having the highest potential.","ai_generated":true,"unit":"iisd-002604#insight-2","date_modified":"2026-10-23"},{"text":"Wetlands offer a maximum one-year sequestration rate of 975,000 tCO2e based on an assumed addition of 300,000 hectares, though they risk becoming a carbon source if loss rates exceed restoration rates.","ai_generated":true,"unit":"iisd-002604#insight-3","date_modified":"2026-10-23"},{"text":"Forestry and riparian buffers combined provide a significant sequestration potential of 493,140 tCO2e under the maximum one-year approach, despite covering a relatively small additional area of 75,000 hectares.","ai_generated":true,"unit":"iisd-002604#insight-4","date_modified":"2026-10-23"},{"text":"Perennial crops have a higher sequestration rate than minimum tillage and cover crops, providing a maximum one-year sequestration rate of 203,685 tCO2e.","ai_generated":true,"unit":"iisd-002604#insight-5","date_modified":"2026-10-23"},{"text":"Minimum tillage, while having a large adoption area of 1 million hectares, has a lower practice sequestration rate of 0.30 tCO2e/ha/year, resulting in a maximum one-year rate of 300,000 tCO2e.","ai_generated":true,"unit":"iisd-002604#insight-6","date_modified":"2026-10-23"},{"text":"The analyzed land use practices strongly align with the priority beneficial management practices (BMPs) of Manitoba's Growing Outcomes in Watersheds (GROW) program, which aims for enhanced carbon storage and improved climate resiliency.","ai_generated":true,"unit":"iisd-002604#insight-7","date_modified":"2026-10-23"}],"climate_tags":["carbon sequestration","greenhouse gas emissions","afforestation","reforestation","land use"],"geography_discussed":["Canada","Alberta"],"frame_perspective":[],"analysis_type":["quantitative analysis","modelling"]},{"id":"sei-001280","url":"https://climateinsightsdirectory.org/document/sei-001280","title":"Climate finance for the Indian Ocean and African Small Island Developing States","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2017-12","source_url":"https://www.sei.org/wp-content/uploads/2018/03/climate-finance-for-the-indian-ocean-and-african-small-island-developing-states.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"Between 2010 and 2015, US$ 978 million in climate finance was committed to seven Indian Ocean and African SIDS, with 83% of these funds concentrated in Cape Verde and Mauritius. The financing was dominated by bilateral ODA loans (74%) and primarily targeted mitigation (56%) over adaptation (42%). Sectoral focus was narrow, concentrating on water and sanitation, energy, and general environmental protection, while critical resilience sectors like health, education, and agriculture were largely ignored. Disbursement rates were notably low, with only 39% of committed funds actually spent across the region, a rate significantly lower than for non-climate ODA.","ai_generated":true,"unit":"sei-001280#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Between 2010 and 2015, US$ 978 million was committed to seven Indian Ocean and African SIDS for the principal purpose of addressing climate change, representing approximately 17% of total ODA for these states.","ai_generated":true,"unit":"sei-001280#insight-1","date_modified":"2026-10-23"},{"text":"Climate finance distribution was highly uneven, with Cape Verde (US$ 365 million) and Mauritius (US$ 448 million) receiving 83% of the total regional climate finance. Conversely, Least Developed Countries (LDCs) in the region—the Comoros, Guinea-Bissau, and São Tomé and Príncipe—received the lowest total and per capita funding.","ai_generated":true,"unit":"sei-001280#insight-2","date_modified":"2026-10-23"},{"text":"The majority of climate finance was provided as debt rather than grants, with concessional loans accounting for US$ 727 million (nearly 75%) of total flows. France and Japan were the largest providers of these loans.","ai_generated":true,"unit":"sei-001280#insight-3","date_modified":"2026-10-23"},{"text":"Regional funding was skewed toward mitigation (56%, US$ 543 million) compared to adaptation (42%, US$ 412 million), with only 2% targeting both objectives.","ai_generated":true,"unit":"sei-001280#insight-4","date_modified":"2026-10-23"},{"text":"Climate finance was concentrated in a narrow range of sectors: water and sanitation (US$ 345 million), energy (US$ 322 million), and 'general environmental protection' (US$ 245 million). Critical resilience sectors such as health, education, agriculture, and disaster-risk reduction received little to no funding.","ai_generated":true,"unit":"sei-001280#insight-5","date_modified":"2026-10-23"},{"text":"The delivery of climate finance was overwhelmingly project-based, accounting for 91% of total flows, while sector budget support made up only 7%.","ai_generated":true,"unit":"sei-001280#insight-6","date_modified":"2026-10-23"},{"text":"There is a significant gap between committed and disbursed funds; only 39% (US$ 384 million) of total commitments were disbursed between 2010 and 2015. This disbursement ratio is significantly lower than that of non-climate ODA for the same countries.","ai_generated":true,"unit":"sei-001280#insight-7","date_modified":"2026-10-23"},{"text":"Bilateral sources dominated the funding landscape, providing approximately 90% (US$ 881 million) of the climate finance, while multilateral sources accounted for only 10% (US$ 97 million).","ai_generated":true,"unit":"sei-001280#insight-8","date_modified":"2026-10-23"}],"climate_tags":["climate finance","climate change adaptation","climate change mitigation","renewable energy","disaster risk reduction","Small Island Developing States"],"geography_discussed":["France","Japan","Portugal","United Arab Emirates","United States"],"frame_perspective":[],"analysis_type":["quantitative analysis","policy analysis"]},{"id":"catf-000644","url":"https://climateinsightsdirectory.org/document/catf-000644","title":"Fumes Across the Fence-Line","publisher":{"name":"Clean Air Task Force","organization":"clean-air-task-force"},"document_type":"report","language":"en","date_published":"2017-11","source_url":"https://cdn.catf.us/wp-content/uploads/2017/11/21092330/catf-rpt-naacp-4.21.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report quantifies the health risks faced by millions of African Americans living near oil and gas infrastructure, highlighting elevated cancer risks and asthma attacks. It details the role of systemic oppression in siting polluting facilities in communities of color and calls for stricter EPA regulations and a transition to a clean energy economy.","ai_generated":true,"unit":"catf-000644#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Over 1 million African Americans live within a half-mile radius of active oil and gas facilities, including wells, compressors, and processing plants.","ai_generated":true,"unit":"catf-000644#insight-1","date_modified":"2026-10-23"},{"text":"More than 1 million African Americans reside in counties where the cancer risk from toxic emissions from natural gas facilities exceeds the U.S. EPA's level of concern.","ai_generated":true,"unit":"catf-000644#insight-2","date_modified":"2026-10-23"},{"text":"Ozone smog resulting from natural gas emissions is associated with approximately 138,000 asthma attacks and 101,000 lost school days for African American children annually.","ai_generated":true,"unit":"catf-000644#insight-3","date_modified":"2026-10-23"},{"text":"Approximately 6.7 million African Americans live in the 91 U.S. counties that contain oil refineries.","ai_generated":true,"unit":"catf-000644#insight-4","date_modified":"2026-10-23"},{"text":"The report argues that the siting of polluting facilities in African American communities is a result of systemic oppression and environmental racism, as companies often target areas with low political power to reduce permit transaction costs.","ai_generated":true,"unit":"catf-000644#insight-5","date_modified":"2026-10-23"},{"text":"Air pollution from oil and gas facilities can impact communities far downwind from the source; for example, emissions from Pennsylvania, West Virginia, and Ohio have contributed to elevated ethane levels and smog in the Baltimore-Washington D.C. corridor.","ai_generated":true,"unit":"catf-000644#insight-6","date_modified":"2026-10-23"},{"text":"The report identifies specific toxic pollutants from the industry, including benzene (linked to cancer and blood disorders), ethylbenzene (respiratory and neurological disorders), hydrogen sulfide (respiratory irritation), and formaldehyde (cancer and respiratory symptoms).","ai_generated":true,"unit":"catf-000644#insight-7","date_modified":"2026-10-23"},{"text":"The authors state that at least 75 percent of existing oil and gas wells and infrastructure remain virtually unregulated, and they urge the EPA to implement comprehensive standards for all facilities rather than just new or modified ones.","ai_generated":true,"unit":"catf-000644#insight-8","date_modified":"2026-10-23"}],"climate_tags":["methane","air pollution","environmental justice","environmental racism","energy transition"],"geography_discussed":["Texas","Louisiana","Oklahoma","California","Pennsylvania","West Virginia","Ohio","North Carolina","Virginia","Baltimore","Port Arthur","Baton Rouge","Philadelphia","East Bay"],"frame_perspective":[],"analysis_type":["quantitative analysis","case study","policy review"]},{"id":"newclim-000218","url":"https://climateinsightsdirectory.org/document/newclim-000218","title":"States, cities and businesses leading the way: a first look at decentralized climate commitments in the US","publisher":{"name":"NewClimate Institute","organization":"newclimate-institute"},"document_type":"report","language":"en","date_published":"2017-09-13","source_url":"http://www.newclimate.org/resources/publications/states-cities-and-businesses-leading-the-way-a-first-look-at-decentralized","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"An analysis of 342 decentralized commitments indicates that the US could meet half of its Paris Agreement climate goals by 2025 if these targets are implemented, with states providing the largest volume of reductions and businesses setting the steepest targets.","ai_generated":true,"unit":"newclim-000218#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The implementation of 342 analyzed commitments from states, cities, and businesses could enable the United States to achieve 50% of its climate commitments under the Paris Agreement by 2025.","ai_generated":true,"unit":"newclim-000218#insight-1","date_modified":"2026-10-23"},{"text":"US states are the primary drivers of emissions reductions in volume, accounting for over two-thirds of the total estimated reductions, with New York, California, and Colorado identified as the largest contributors.","ai_generated":true,"unit":"newclim-000218#insight-2","date_modified":"2026-10-23"},{"text":"While states provide the most volume, cities and businesses show higher ambition in their targets; cities average a 22% greenhouse gas reduction between 2015 and 2025, and businesses target a 25% reduction over the next decade.","ai_generated":true,"unit":"newclim-000218#insight-3","date_modified":"2026-10-23"}],"climate_tags":["greenhouse gas emissions","Paris Agreement"],"geography_discussed":["New York","California","Colorado"],"frame_perspective":[],"analysis_type":["quantitative analysis"]},{"id":"prio-001221","url":"https://climateinsightsdirectory.org/document/prio-001221","title":"ATT MONITOR REPORT 2017","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"report","language":"en","date_published":"2017-09-11","source_url":"https://cdn.cloud.prio.org/files/4e9e3fc9-bff2-463c-ab66-4edcfe4e742d/ATT Monitor 2017.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The ATT Monitor 2017 report finds that while the Arms Trade Treaty (ATT) has seen steady universalization, progress in public reporting is disappointing in both quantity and quality. Analysis of 2015 Annual Reports reveals significant discrepancies between reported exports and imports, with only 6% of analyzed small arms and light weapons (SALW) transactions being exactly mirrored. The report highlights a critical gap between reported implementation measures in Initial Reports and actual practice on the ground. It also introduces the 'Risk Watch' tool, which uses a typology of individual, group, institutional, and conflict violence to identify contexts where arms transfers may fuel human rights abuses.","ai_generated":true,"unit":"prio-001221#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"As of 31 May 2017, 92 countries were States Parties to the ATT, representing 48 per cent of all UN member states, though the pace of new membership slowed by more than 50 per cent compared to the previous year.","ai_generated":true,"unit":"prio-001221#insight-1","date_modified":"2026-10-23"},{"text":"The ATT Voluntary Trust Fund (VTF), established by CSP 2016 to support national implementation, had received approximately US$1.6 million in contributions and US$370,139 in pledges by the end of May 2017.","ai_generated":true,"unit":"prio-001221#insight-2","date_modified":"2026-10-23"},{"text":"Compliance with mandatory reporting is low; by 31 May 2017, only 58 of 82 required Initial Reports (72%) had been received, and only 31 of 75 expected Annual Reports (41%) were submitted by 7 June 2017.","ai_generated":true,"unit":"prio-001221#insight-3","date_modified":"2026-10-23"},{"text":"A cross-check of 435 SALW transactions from 17 major exporting States Parties showed that only 6% were exactly mirrored by the importing state, and 78% of reported exports had no corresponding import of a similar weapon type.","ai_generated":true,"unit":"prio-001221#insight-4","date_modified":"2026-10-23"},{"text":"Significant reporting discrepancies were noted between Poland and the Czech Republic; Poland reported exporting 12,210 units of various SALW to the Czech Republic, but the Czech Republic reported no SALW imports from Poland.","ai_generated":true,"unit":"prio-001221#insight-5","date_modified":"2026-10-23"},{"text":"Some States Parties reported 'nil' imports while other countries reported exporting arms to them; for example, Ireland reported nil imports, but Belgium, Germany, Sweden, and the UK reported exports to Ireland.","ai_generated":true,"unit":"prio-001221#insight-6","date_modified":"2026-10-23"},{"text":"The report identifies a 'critical gap' between the implementation measures described in Initial Reports and actual practices on the ground, noting that some states signal an intent to act rather than existing practice.","ai_generated":true,"unit":"prio-001221#insight-7","date_modified":"2026-10-23"},{"text":"Regarding export controls, 89% of reporting States Parties indicate their national control system covers all eight categories of conventional arms under Article 2.1, but 7% claim their system lacks risk assessment processes because they are not arms-exporting states.","ai_generated":true,"unit":"prio-001221#insight-8","date_modified":"2026-10-23"},{"text":"The 'Risk Watch' tool uses a typology of four violence categories—Individual, Group, Institutional, and Conflict—to identify contexts of concern for arms misuse, drawing on sources like the Global Terrorism Index and the Political Terror Scale.","ai_generated":true,"unit":"prio-001221#insight-9","date_modified":"2026-10-23"},{"text":"The report argues that transparency is essential for preventing the diversion of arms, noting that diversion often occurs due to weak governmental structures and lack of accountability.","ai_generated":true,"unit":"prio-001221#insight-10","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Yemen","United Kingdom","Saudi Arabia","South Sudan","Poland","Czech Republic"],"frame_perspective":[],"analysis_type":["compliance assessment","quantitative analysis","qualitative analysis","policy review"]},{"id":"sei-001907","url":"https://climateinsightsdirectory.org/document/sei-001907","title":"Climate finance in the Caribbean region’s Small Island Developing States","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2017-09","source_url":"https://www.sei.org/mediamanager/documents/Publications/SEI-WP-2017-climate-finance-caribbean.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"Between 2010 and 2015, US$ 1,477 million in climate finance was committed to Caribbean SIDS, representing approximately 6% of total reported aid flows. The analysis reveals a heavy reliance on bilateral sources (85%), with a significant concentration of funds in a few countries and sectors. While 48% of finance targeted mitigation and 32% adaptation, the report highlights a critical gap in funding for resilience-essential sectors like health and education. Furthermore, a low regional disbursement ratio of 39% suggests significant implementation challenges compared to non-climate aid.","ai_generated":true,"unit":"sei-001907#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"A total of US$ 1,477 million in climate finance was committed to Caribbean SIDS between 2010 and 2015, which constitutes approximately 6% of the total reported aid flows to the region during that period.","ai_generated":true,"unit":"sei-001907#insight-1","date_modified":"2026-10-23"},{"text":"Climate finance distribution is highly concentrated; 52% of the total committed finance for the region came from just two funding relationships: Norway's grants to Guyana and France's loans to the Dominican Republic.","ai_generated":true,"unit":"sei-001907#insight-2","date_modified":"2026-10-23"},{"text":"The majority of climate finance (85%) originated from bilateral sources, while multilateral sources contributed 15%. Within the multilateral category, the World Bank's Climate Investment Funds (CIFs) were the most significant contributors.","ai_generated":true,"unit":"sei-001907#insight-3","date_modified":"2026-10-23"},{"text":"Funding is split between mitigation (48%), adaptation (32%), and projects targeting both (20%). Most countries received more for adaptation than mitigation, with the exceptions of Cuba, the Dominican Republic, Grenada, and Guyana.","ai_generated":true,"unit":"sei-001907#insight-4","date_modified":"2026-10-23"},{"text":"Climate finance is predominantly project-based (77%), with 20% delivered as contributions to special-purpose programs and funds, and only 1.3% provided as sector budget support.","ai_generated":true,"unit":"sei-001907#insight-5","date_modified":"2026-10-23"},{"text":"There is a significant misalignment between climate finance and long-term resilience needs; while 'general environment protection' received the most funding, critical sectors such as health and education received no climate finance, and agriculture received very little.","ai_generated":true,"unit":"sei-001907#insight-6","date_modified":"2026-10-23"},{"text":"Disbursement of climate finance is notably inefficient compared to other aid. Only 39% of committed climate finance was actually disbursed between 2010 and 2015, whereas non-climate aid flows had a disbursement ratio of 95%.","ai_generated":true,"unit":"sei-001907#insight-7","date_modified":"2026-10-23"},{"text":"Financial instruments vary by donor: 62% of regional climate finance was provided as grants and 38% as loans. France and the World Bank CIFs were the primary providers of concessional loans.","ai_generated":true,"unit":"sei-001907#insight-8","date_modified":"2026-10-23"}],"climate_tags":["climate finance","climate change adaptation","climate change mitigation","renewable energy","disaster risk reduction","urbanization","Reducing emissions from deforestation and forest degradation","Small Island Developing States"],"geography_discussed":["Guyana","Dominican Republic","Haiti","Cuba","Jamaica","Dominica","Saint Lucia","Suriname","Antigua and Barbuda","Grenada","Saint Vincent and the Grenadines","Saint Kitts and Nevis","Barbados","Trinidad and Tobago"],"frame_perspective":[],"analysis_type":["quantitative analysis","financial flow analysis"]},{"id":"ucs-000200","url":"https://climateinsightsdirectory.org/document/ucs-000200","title":"Tracing Who’s Responsible for Temperature Increase and Sea Level Rise","publisher":{"name":"Union of Concerned Scientists","organization":"union-of-concerned-scientists"},"document_type":"fact sheet","language":"en","date_published":"2017-08-17","source_url":"https://www.ucs.org/resources/tracing-whos-responsible-temperature-increase-and-sea-level-rise","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document details findings from a study published in Climatic Change that attributes specific percentages of global warming and sea level rise to the largest carbon producers. It highlights that the 90 largest producers contributed 57% of the atmospheric carbon dioxide rise since 1880, while 50 investor-owned companies were responsible for roughly 16% of the temperature increase and 11% of sea level rise over the same period. The text argues that these companies knew of the risks as early as 1965 but chose to misinform the public.","ai_generated":true,"unit":"ucs-000200#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The 90 largest carbon producers are responsible for 57% of the increase in atmospheric carbon dioxide since 1880, nearly 50% of the rise in global average temperature, and approximately 30% of global sea level rise relative to 1880 levels.","ai_generated":true,"unit":"ucs-000200#insight-1","date_modified":"2026-10-23"},{"text":"Fifty investor-owned carbon producers, including Shell, BP, ExxonMobil, Chevron, Total, ConocoPhillips, and Peabody, caused roughly 16% of the global average temperature increase and around 11% of the global sea level rise from 1880 to 2010.","ai_generated":true,"unit":"ucs-000200#insight-2","date_modified":"2026-10-23"},{"text":"Between 1980 and 2010, a period during which fossil fuel companies were aware of the warming caused by their products, the same 50 investor-owned companies contributed approximately 10% of the global average temperature increase and about 4% of the sea level rise.","ai_generated":true,"unit":"ucs-000200#insight-3","date_modified":"2026-10-23"},{"text":"Investor-owned fossil fuel companies were aware as early as 1965 that their products released carbon dioxide and methane emissions capable of destabilizing the climate, yet they chose to block emissions limits and misinform investors and the public.","ai_generated":true,"unit":"ucs-000200#insight-4","date_modified":"2026-10-23"}],"climate_tags":["carbon dioxide","methane emissions","sea level rise","fossil fuel industry","climate change adaptation"],"geography_discussed":["New York City"],"frame_perspective":[],"analysis_type":["attribution study","quantitative analysis"]},{"id":"sei-000834","url":"https://climateinsightsdirectory.org/document/sei-000834","title":"Livestock manure management practices Bangladesh","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2017-07-06","source_url":"https://www.sei.org/publications/livestock-manure-management-practices-bangladesh/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The study analyzes manure management in Bangladesh, finding that the majority of large ruminant manure is kept in solid storage or used as fuel. It calculates specific methane emission factors for various livestock types and identifies farmer unawareness and credit constraints as primary barriers to improved management.","ai_generated":true,"unit":"sei-000834#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Large ruminant manure management is dominated by solid storage (56.2% to 57.0%) and use as burned fuel (37.3% to 43.0%), while anaerobic digestion accounts for only 4.80% and liquid slurry loss for 1.65%.","ai_generated":true,"unit":"sei-000834#insight-1","date_modified":"2026-10-23"},{"text":"Methane emission factors vary by animal type, with dairy and other cattle at 6.77 Kg CH4/head/year, buffalo at 6.41, small ruminants at 5.42, poultry at 0.024, and other cattle (bulls and growing animals) at 0.203 Kg CH4/head/year.","ai_generated":true,"unit":"sei-000834#insight-2","date_modified":"2026-10-23"},{"text":"The primary obstacles preventing the adoption of improved manure management practices are a lack of farmer awareness, limited capacity, and credit problems.","ai_generated":true,"unit":"sei-000834#insight-3","date_modified":"2026-10-23"}],"climate_tags":["methane emissions","agriculture"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["quantitative analysis","survey"]},{"id":"prio-001858","url":"https://climateinsightsdirectory.org/document/prio-001858","title":"Which Groups Fight?","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":"2017-05-30","source_url":"https://cdn.cloud.prio.org/files/a4531ecd-28b3-4453-ac2c-1e96ebfdd740/Which groups fight Customary institutions and communal conflicts in Africa.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The research examines 143 African ethnic groups to determine if customary institutions influence communal violence. It finds that groups with more formalized customary institutions—such as courts, legislatures, and chiefs—are significantly less likely to be involved in both inter-communal and intra-communal conflicts. The authors argue these institutions facilitate credible bargaining and mediation. In contrast, the study finds only weak and non-robust evidence that the inclusiveness or 'democratic' nature of these institutions reduces conflict.","ai_generated":true,"unit":"prio-001858#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Ethnic groups with a higher degree of formalized customary institutions are less prone to communal conflict, both internally and with other groups.","ai_generated":true,"unit":"prio-001858#insight-1","date_modified":"2026-10-23"},{"text":"Formal customary institutions are believed to pacify groups by reducing uncertainty and providing mechanisms for credible non-violent bargaining and internal mediation.","ai_generated":true,"unit":"prio-001858#insight-2","date_modified":"2026-10-23"},{"text":"The presence of formal institutions reduces the risk of conflict by limiting the potential for 'spoilers' and allowing groups to impose 'hand-tying' costs on themselves to ensure agreements are kept.","ai_generated":true,"unit":"prio-001858#insight-3","date_modified":"2026-10-23"},{"text":"Simulated data indicates that increasing the number of formal customary institutions from the minimum to the maximum value can decrease the probability of a group experiencing at least one communal conflict from 42% to approximately 10%.","ai_generated":true,"unit":"prio-001858#insight-4","date_modified":"2026-10-23"},{"text":"There is some evidence that inclusive political structures (larger selectorates) are associated with less conflict, but this finding is much weaker and less robust than the effect of formalization.","ai_generated":true,"unit":"prio-001858#insight-5","date_modified":"2026-10-23"},{"text":"The study challenges previous arguments that customary institutions increase conflict risk, suggesting instead that they often serve as essential substitutes for weak state governance in conflict mediation.","ai_generated":true,"unit":"prio-001858#insight-6","date_modified":"2026-10-23"},{"text":"The negative relationship between formal customary institutions and communal conflict remains stable even when controlling for physical environment, agricultural history, cultural aspects, and economic fortunes.","ai_generated":true,"unit":"prio-001858#insight-7","date_modified":"2026-10-23"}],"climate_tags":["governance"],"geography_discussed":["South Sudan","Ghana","Namibia","Uganda","South Africa","Ethiopia","Sierra Leone","Algeria"],"frame_perspective":[],"analysis_type":["quantitative analysis","cross-sectional study","logit model","linear model"]}]}