{"query_echo":{"q":"","filters":{"geography":["Delhi"]},"warnings":[]},"total":{"value":105,"relation":"eq"},"page":6,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?geography=Delhi&page=6","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":"wri-000138","url":"https://climateinsightsdirectory.org/document/wri-000138","title":"Public Bicycle Sharing in India: Lessons Learned from Implementation in Three Cities","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://www.wri.org/research/public-bicycle-sharing-india-lessons-learned-implementation-three-cities","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document analyzes the evolution of public bicycle-sharing (PBS) in India, noting a decline in cycling mode share from nearly 30 percent in 1994 to an average of 11 percent in 2007. While early private rental models in cities like Mumbai, Delhi, and Bangalore failed due to economic unviability, systems launched in 2017 in Mysuru, Bhopal, and Pune have been more successful by utilizing public-private partnerships, smart technology, and public sector support. The paper highlights the role of the National Urban Transport Policy in promoting non-motorized transport to counter the social stigma of cycling as a 'poor man's mode of transport'.","ai_generated":true,"unit":"wri-000138#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The national mode share for bicycles in India experienced a significant decline, dropping from nearly 30 percent in 1994 to an average of 11 percent by 2007.","ai_generated":true,"unit":"wri-000138#insight-1","date_modified":"2026-10-23"},{"text":"Early attempts to implement PBS in Mumbai, Delhi, and Bangalore failed within months because they relied on completely private rental models that were economically unviable, with government support limited to providing land.","ai_generated":true,"unit":"wri-000138#insight-2","date_modified":"2026-10-23"},{"text":"The PBS systems introduced in 2017 in Mysuru, Bhopal, and Pune have been more successful and sustainable than previous attempts due to the use of public-private partnerships, smart technology, and quality service incentives.","ai_generated":true,"unit":"wri-000138#insight-3","date_modified":"2026-10-23"},{"text":"Cycling in India has been hindered by rapid motorization and a specific social stigma that characterizes it as a mode of transport for the poor.","ai_generated":true,"unit":"wri-000138#insight-4","date_modified":"2026-10-23"}],"climate_tags":["urban transport","public–private partnership"],"geography_discussed":["Mysore","Bhopal","Pune","Mumbai","Delhi","Bengaluru","Amsterdam"],"frame_perspective":[],"analysis_type":["case study","policy analysis"]},{"id":"wri-000253","url":"https://climateinsightsdirectory.org/document/wri-000253","title":"Renewable Energy Procurement Perceptions among Commercial and Industrial Consumers: Current Practices and Future Possibilities","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://www.wri.org/research/renewable-energy-procurement-perceptions-among-commercial-and-industrial-consumers","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The research examines renewable energy (RE) procurement among 101 corporate and 185 SME consumers across five Indian states. It finds a dominant preference for on-site solutions, with large corporations favoring open access off-site projects due to higher capital and energy needs. Green Tariffs (GTs) face low awareness—up to 82% of corporate consumers and 94% of SMEs are unaware of them—and poor acceptability, as 62% of corporate and 55% of SME consumers are unwilling to pay a premium for GTs. The paper recommends that state energy departments restructure GT models with lower premiums and fiscal incentives, while utilities should act as information disseminators to prevent C&I consumers from migrating from the grid.","ai_generated":true,"unit":"wri-000253#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Commercial and industrial (C&I) consumers show a primary preference for on-site renewable energy solutions. Large corporations specifically favor open access (OA) off-site projects because they possess greater capital, have larger energy requirements, and can manage the procedural complexities associated with OA transactions.","ai_generated":true,"unit":"wri-000253#insight-1","date_modified":"2026-10-23"},{"text":"Awareness of Green Tariffs (GTs) is very low among C&I consumers, with up to 94 percent of SMEs and 82 percent of corporate consumers unaware of the concept. Those aware of GTs generally hold negative perceptions, citing concerns over the longevity of premiums, the certainty of 100 percent RE-based supply from DISCOMs, and RE additionality.","ai_generated":true,"unit":"wri-000253#insight-2","date_modified":"2026-10-23"},{"text":"There is low willingness to pay (WTP) for premium-based Green Tariffs, with 62 percent of corporate consumers and 55 percent of SME consumers unwilling to pay any premium. Despite this, SMEs are more open to GTs than corporations because GTs allow them to access RE without the heavy capital investments required for on-site solutions or the complexity of off-site OA transactions.","ai_generated":true,"unit":"wri-000253#insight-3","date_modified":"2026-10-23"}],"climate_tags":["power purchase agreement","energy transition"],"geography_discussed":["Andhra Pradesh","Karnataka","Delhi"],"frame_perspective":[],"analysis_type":["qualitative interview study","contingent valuation experiment"]},{"id":"wri-000564","url":"https://climateinsightsdirectory.org/document/wri-000564","title":"Urban Blue-Green Conundrum: A 10-City Study on the Impacts of Urbanization on Natural Infrastructure in India","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://www.wri.org/research/urban-blue-green-conundrum-10-city-study-impacts-urbanization-natural-infrastructure-india","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study analyzes the impact of urbanization on natural infrastructure in 10 major Indian cities from 2000 to 2015, finding significant increases in built-up areas and a corresponding loss of surface water and groundwater recharge potential. It advocates for an integrated urban blue-green approach to planning to mitigate risks like urban flooding and water scarcity.","ai_generated":true,"unit":"wri-000564#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Between 2000 and 2015, the built-up area in the 10 studied cities grew by an average of 47 percent within 0–20 km of the city center and 134 percent in the periphery (20–50 km).","ai_generated":true,"unit":"wri-000564#insight-1","date_modified":"2026-10-23"},{"text":"The 10 cities experienced an estimated loss of 307 sq. km of surface water between 2000 and 2015, representing a 15 percent decrease.","ai_generated":true,"unit":"wri-000564#insight-2","date_modified":"2026-10-23"},{"text":"Approximately 44 percent (1,177 sq. km) of new development in the 0–50 km urban region of the study cities occurred on areas with very high or high recharge potential between 2000 and 2015.","ai_generated":true,"unit":"wri-000564#insight-3","date_modified":"2026-10-23"},{"text":"Urbanization disconnected from the natural environment leads to negative outcomes including urban flooding, water scarcity, and increased groundwater stress, often because development is sited on vulnerable zones like lake beds, floodplains, and low-lying areas.","ai_generated":true,"unit":"wri-000564#insight-4","date_modified":"2026-10-23"}],"climate_tags":["urbanization","green infrastructure","groundwater recharge","urban flooding","water scarcity","urban planning"],"geography_discussed":["Ahmedabad","Bengaluru","Chennai","Delhi","Hyderabad","Jaipur","Kolkata","Mumbai","Pune","Surat"],"frame_perspective":[],"analysis_type":["correlation study","spatial analysis"]},{"id":"wri-000648","url":"https://climateinsightsdirectory.org/document/wri-000648","title":"Understanding the Impact of Bus Aggregators on Urban Mobility in India’s National Capital Region","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"briefing","language":"en","date_published":null,"source_url":"https://www.wri.org/research/understanding-impact-bus-aggregators-urban-mobility-indias-national-capital-region","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document assesses the impact of bus aggregators, specifically Shuttl, on urban mobility and emissions in Delhi-NCR, finding that the service reduces CO2 and criteria pollutants without significantly siphoning passengers from public bus services.","ai_generated":true,"unit":"wri-000648#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Shuttl has contributed positively to the environment in Delhi-NCR by reducing annual CO2 emissions by 14,022 tons, as well as reducing criteria pollutants including PM2.5, NOx, CO, and VOC.","ai_generated":true,"unit":"wri-000648#insight-1","date_modified":"2026-10-23"},{"text":"Analysis indicates that Shuttl does not primarily compete with public bus services in Delhi, as less than 2 percent of the surveyed sample transitioned from public buses to Shuttl.","ai_generated":true,"unit":"wri-000648#insight-2","date_modified":"2026-10-23"}],"climate_tags":["urban transport","greenhouse gas emissions","public transport"],"geography_discussed":["India","Delhi"],"frame_perspective":[],"analysis_type":["environmental impact assessment"]},{"id":"wwatt-000113","url":"https://climateinsightsdirectory.org/document/wwatt-000113","title":"Climate Change made devastating early heat in India and Pakistan 30 times more likely","publisher":{"name":"World Weather Attribution","organization":"world-weather-attribution"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://www.worldweatherattribution.org/wp-content/uploads/India_Pak-Heatwave-scientific-report.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study concludes that human-induced climate change made the March-April 2022 heatwave in India and Pakistan approximately 30 times more likely and about 1\u0001C hotter than in a pre-industrial climate. The event, defined as a 1-in-100-year occurrence in today's climate, caused at least 90 deaths, triggered glacial lake outburst floods in northern Pakistan, and led to significant wheat crop yield losses in India, prompting a wheat export ban. The researchers warn that at 2\u0001C of global warming, such heatwaves will become an additional factor of 2-20 more likely and 0.5-1.5\u0001C hotter. Vulnerability is highest among outdoor daily wage earners and urban poor in informal settlements, though the report notes that Heat Action Plans in India, now covering 130 cities, can effectively reduce mortality.","ai_generated":true,"unit":"wwatt-000113#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Human-caused climate change increased the probability of the 2022 heatwave by a factor of approximately 30, and the event would have been about 1\u0001C cooler in a pre-industrial climate.","ai_generated":true,"unit":"wwatt-000113#insight-1","date_modified":"2026-10-23"},{"text":"The 2022 heatwave is estimated to have caused at least 90 deaths across India and Pakistan, though this number is expected to rise.","ai_generated":true,"unit":"wwatt-000113#insight-2","date_modified":"2026-10-23"},{"text":"The heatwave caused significant agricultural damage, including a 20% shortfall in all-India wheat yield, which led the Indian government to ban most wheat exports to protect domestic food security.","ai_generated":true,"unit":"wwatt-000113#insight-3","date_modified":"2026-10-23"},{"text":"The event triggered secondary disasters, including an extreme Glacial Lake Outburst Flood (GLOF) in northern Pakistan's Hunza valley on May 7 and approximately 300 large forest fires in India on April 28.","ai_generated":true,"unit":"wwatt-000113#insight-4","date_modified":"2026-10-23"},{"text":"Future warming to a global mean temperature of +2\u0001C is projected to make such heatwaves an additional factor of 2-20 more likely and 0.5-1.5\u0001C hotter than in 2022.","ai_generated":true,"unit":"wwatt-000113#insight-5","date_modified":"2026-10-23"},{"text":"The 2022 event was characterized as a \"dry heatwave\" due to significantly below-average rainfall and humidity, which reduced the relative importance of humidity for health impacts compared to late-season or coastal heatwaves.","ai_generated":true,"unit":"wwatt-000113#insight-6","date_modified":"2026-10-23"},{"text":"Urban poor in informal settlements are disproportionately affected due to housing materials like tin roofs that intensify indoor temperatures and the urban heat island effect, which can increase local heat by up to 12\u0001C.","ai_generated":true,"unit":"wwatt-000113#insight-7","date_modified":"2026-10-23"}],"climate_tags":["heat wave","anthropogenic climate change","glacier lake outburst flood","forest fire","urban heat island","climate change adaptation","food security","informal housing","coal power"],"geography_discussed":["Hunza Valley","Uttarakhand","Delhi","Lahore","Ahmedabad","Nagpur"],"frame_perspective":[],"analysis_type":["attribution study","probabilistic assessment","vulnerability analysis"]}]}