{"query_echo":{"q":"","filters":{"analysis_type":["uncertainty analysis"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'uncertainty analysis' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":4,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=uncertainty+analysis","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":"cdkn-000706","url":"https://climateinsightsdirectory.org/document/cdkn-000706","title":"Pakistan Low Carbon Scenario Analysis: GHG Reference Case Projection - Briefing Note","publisher":{"name":"Climate and Development Knowledge Network","organization":"climate-and-development-knowledge-network"},"document_type":"briefing","language":"en","date_published":"2016-08","source_url":"http://cdkn.org/wp-content/uploads/2016/11/Pakistan-GHG-Emissions-Reference-Case-Briefing-Note-Oct-27.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document establishes a business-as-usual (BAU) GHG emission reference case for Pakistan, projecting emissions from 2000 to 2030. It identifies agriculture as the largest emission source and analyzes how variations in GDP growth and autonomous energy efficiency improvements (AEEI) impact future emission levels. The reference case assumes an average annual GDP growth rate of 6% between 2015 and 2030.","ai_generated":true,"unit":"cdkn-000706#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"In 2012, Pakistan's total GHG emissions were estimated at 365 MtCO2e, with the agriculture sector being the largest contributor at 165 Mt (42% of the total). Other significant contributors included industry (63 Mt), electricity (40 Mt), and transport (35 Mt).","ai_generated":true,"unit":"cdkn-000706#insight-1","date_modified":"2026-10-23"},{"text":"The reference case projection assumes an average annual GDP growth rate of 6% between 2015 and 2030, which is lower than the 8% target set in Pakistan's Vision 2025.","ai_generated":true,"unit":"cdkn-000706#insight-2","date_modified":"2026-10-23"},{"text":"GDP growth is a primary driver of emissions; a scenario with 3% higher GDP growth (modeling a condition where the China-Pakistan Economic Corridor (CPEC) substantially spurs growth) would increase 2030 emissions by 36% (+278 MtCO2e) relative to the baseline.","ai_generated":true,"unit":"cdkn-000706#insight-3","date_modified":"2026-10-23"},{"text":"Variations in autonomous energy efficiency improvements (AEEI) have a smaller impact on 2030 emissions than GDP growth, with a high AEEI scenario (+50%) resulting in a 3% decrease (-19 MtCO2e) and a low AEEI scenario (-50%) resulting in a 3% increase (+20 MtCO2e).","ai_generated":true,"unit":"cdkn-000706#insight-4","date_modified":"2026-10-23"}],"climate_tags":["greenhouse gas emissions","Low carbon development","energy efficiency","agriculture","electricity generation","transportation","Villevocance","petroleum industry"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["scenario analysis","projection","uncertainty analysis"]},{"id":"bc3res-000155","url":"https://climateinsightsdirectory.org/document/bc3res-000155","title":"UNDER WHAT CONDITIONS IS THE BIOETHANOL AND BIODIESEL PRODUCED ENTIRELY IN THE BASQUE COUNTRY SUSTAINABLE?","publisher":{"name":"Basque Centre for Climate Change","organization":"basque-centre-for-climate-change"},"document_type":"policy brief","language":"en","date_published":"2015","source_url":"https://www.bc3research.org/h6T8Uy8Nm4gFs0O/201506091247561731132492.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document evaluates the environmental sustainability of first-generation biofuels produced in the Basque Country using an innovative methodology that integrates the SIMSNIC agronomic model with life cycle analysis. The study focuses on bioethanol from wheat and biodiesel from rapeseed in the La Llanada Alavesa area. It finds that while biofuels are more energy efficient than fossil fuels, meeting the EU's mandatory 35% greenhouse gas (GHG) reduction target is unlikely under current mineral fertilisation conditions, particularly in nitrate-vulnerable areas. Organic fertilisation increases the likelihood of meeting GHG targets but exacerbates water contamination, soil acidification, and land-use competition. The authors conclude that the agricultural stage, specifically nitrogen fertilisation and climatology, is the primary driver of the carbon footprint due to nitrous oxide emissions.","ai_generated":true,"unit":"bc3res-000155#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The agricultural production stage is the most significant contributor to the environmental impact of biofuel production, with nitrous oxide (N2O) emissions from soil being the primary driver of the carbon footprint. These emissions are heavily influenced by the type and dose of fertilisation and local climatology.","ai_generated":true,"unit":"bc3res-000155#insight-1","date_modified":"2026-10-23"},{"text":"Biofuels produced in the study area are consistently more energy efficient than fossil-fuel-based petrol or diesel, but their ability to reduce the carbon footprint depends on specific field handling and the climatological year.","ai_generated":true,"unit":"bc3res-000155#insight-2","date_modified":"2026-10-23"},{"text":"Under current mineral fertilisation conditions in areas vulnerable to nitrate contamination, it is unlikely that wheat-derived ethanol and rapeseed-derived diesel will meet the EU's sustainability requirement of at least a 35% reduction in greenhouse gases compared to fossil fuels.","ai_generated":true,"unit":"bc3res-000155#insight-3","date_modified":"2026-10-23"},{"text":"Organic fertilisation increases the probability of meeting EU GHG sustainability standards compared to mineral fertilisation, but it results in higher water contamination, ecosystem acidification, and greater land-use requirements.","ai_generated":true,"unit":"bc3res-000155#insight-4","date_modified":"2026-10-23"},{"text":"Biofuel production in the Basque Country case study exhibits a significantly higher impact than fossil fuels regarding water contamination and competition for land use. The authors suggest energy crops should only be grown on land without ecological or agricultural interest to avoid competing with food production.","ai_generated":true,"unit":"bc3res-000155#insight-5","date_modified":"2026-10-23"}],"climate_tags":["ethanol fuel","biodiesel","greenhouse gas emissions","carbon footprint","nitrous oxide","land-use change","water pollution"],"geography_discussed":["Spain","European Union"],"frame_perspective":[],"analysis_type":["life cycle analysis","agronomic modelling","uncertainty analysis"]},{"id":"sei-001655","url":"https://climateinsightsdirectory.org/document/sei-001655","title":"European and Global Climate Change Projections","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"policy brief","language":"en","date_published":"2011-09","source_url":"https://www.sei.org/mediamanager/documents/Publications/sei-climatecost-european-and-global-climate-change-projections.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The ClimateCost project analysed three emissions scenarios (A1B, E1, and RCP8.5) to project temperature and precipitation changes. Findings indicate that global temperatures could rise by 2.4°C to 3.4°C by 2071-2100 under the A1B scenario, with Europe experiencing more intense summer warming, particularly in the south. While the E1 mitigation scenario reduces these increases, projections for all scenarios do not significantly diverge until after 2040, emphasizing the need for immediate adaptation. Precipitation projections show higher uncertainty, but suggest wetter winters for Northern Europe and drier conditions for Southern Europe.","ai_generated":true,"unit":"sei-001655#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Under the medium-high emission baseline scenario (A1B), global average temperatures are projected to rise between 1.6°C and 2.3°C by 2041-2070, and between 2.4°C and 3.4°C by 2071-2100, relative to a 1961-1990 baseline.","ai_generated":true,"unit":"sei-001655#insight-1","date_modified":"2026-10-23"},{"text":"European temperature increases are projected to be higher than the global average, especially during the summer. In the A1B scenario, the Iberian Peninsula could see a mean temperature increase of up to 5°C by 2071-2100.","ai_generated":true,"unit":"sei-001655#insight-2","date_modified":"2026-10-23"},{"text":"The E1 mitigation scenario, designed to align with the EU's 2°C global target, limits the projected global temperature increase to approximately 1.5°C by 2071-2100. However, European summer temperatures under this scenario are still projected to increase by more than 2°C, and potentially over 3°C, by 2071-2100.","ai_generated":true,"unit":"sei-001655#insight-3","date_modified":"2026-10-23"},{"text":"The RCP8.5 high-emission scenario is projected to result in global warming of approximately 3.5°C by 2071-2100 relative to the 1961-1990 baseline.","ai_generated":true,"unit":"sei-001655#insight-4","date_modified":"2026-10-23"},{"text":"Climate projections for different emission pathways do not diverge significantly until after 2040, with mean global temperatures projected to increase by about 1°C by 2011-2040 regardless of the pathway, indicating that early warming is already 'locked-in'.","ai_generated":true,"unit":"sei-001655#insight-5","date_modified":"2026-10-23"},{"text":"Precipitation projections are more uncertain than temperature projections, but show robust regional patterns: Northern and Western Europe are projected to have wetter winters, while Southern Europe is projected to be drier year-round, with summer precipitation potentially reduced by 50% by the end of the century.","ai_generated":true,"unit":"sei-001655#insight-6","date_modified":"2026-10-23"},{"text":"There is significant structural and statistical uncertainty in climate modelling, particularly regarding precipitation and regional changes. The project argues that this uncertainty should be quantified and used to plan robust strategies rather than as a justification for inaction.","ai_generated":true,"unit":"sei-001655#insight-7","date_modified":"2026-10-23"}],"climate_tags":["climate change adaptation","climate change mitigation"],"geography_discussed":["Iberian Peninsula","Northern Europe","Southern Europe","Western Europe","Eastern Europe"],"frame_perspective":[],"analysis_type":["climate projection","uncertainty analysis"]},{"id":"cer-001162","url":"https://climateinsightsdirectory.org/document/cer-001162","title":"matimba-health-risk-assessment_8-64d754a8a3e40115.pdf","publisher":{"name":"Centre for Environmental Rights","organization":"centre-for-environmental-rights"},"document_type":"report","language":"en","date_published":null,"source_url":"https://cer.org.za/wp-content/uploads/2014/07/Matimba-Health-Risk-Assessment_8.pdf?x21779","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"This report, prepared by INFOTOX (Pty) Ltd for Eskom Holdings, evaluates the confidence levels and uncertainties associated with the health risk assessment of particulate matter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2) emissions from Eskom operations. It concludes that risk quantifications based on mortality and particulate matter are more reliable than those based on hospitalisation and gaseous pollutants.","ai_generated":true,"unit":"cer-001162#summary","date_modified":"2026-08-17"},"key_insights":[{"text":"The report identifies four general uncertainties applicable to all studies estimating the burden of disease from outdoor air pollution: the actual magnitude of mortality effects and their confidence intervals, the shape of the concentration-response function (linear vs. log-linear) and the existence of threshold concentrations, the influence of co-pollutants, and the baseline rates of health outcomes in the studied population.","ai_generated":true,"unit":"cer-001162#insight-1","date_modified":"2026-08-17"},{"text":"Confidence in the concentration-response functions for particulate matter (PM) is rated higher than for gaseous pollutants because PM has been subject to more extensive global research, including a WHO meta-analysis of 629 ecological time series and 160 individual or panel studies.","ai_generated":true,"unit":"cer-001162#insight-2","date_modified":"2026-08-17"},{"text":"Estimates of mortality are considered more valid than estimates of hospitalisation. This is because the WHO provides a reasonable basis for applying mortality relative risks globally, whereas hospitalisation data is scarce for non-industrialised nations and difficult to relate to the ultimate disease burden.","ai_generated":true,"unit":"cer-001162#insight-3","date_modified":"2026-08-17"},{"text":"There is a lower degree of confidence in the baseline hospitalisation data used for the Eskom assessment compared to mortality data. Mortality data is supported by the South African National Burden of Disease Study 2000, while hospitalisation numbers were extrapolated from a study in KwaZulu-Natal, which may not be representative of Mpumalanga and Gauteng due to different industrial profiles and HIV-AIDS prevalence rates.","ai_generated":true,"unit":"cer-001162#insight-4","date_modified":"2026-08-17"},{"text":"The report concludes that while hospitalisation numbers can be used for decision-making and comparing mitigation options, they should be interpreted with caution as they likely possess a wide confidence interval, meaning actual numbers in receptor communities could be considerably higher or lower than predicted.","ai_generated":true,"unit":"cer-001162#insight-5","date_modified":"2026-08-17"}],"climate_tags":["air quality","particulate matter","health risk assessment","energy transition","power plants"],"geography_discussed":["KwaZulu-Natal","Mpumalanga","Gauteng"],"frame_perspective":[],"analysis_type":["Risk Characterisation","Literature Review","Uncertainty Analysis"]}]}