{"query_echo":{"q":"","filters":{"geography":["Jabodetabek"]},"warnings":[]},"total":{"value":5,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?geography=Jabodetabek","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"ember-000163","url":"https://climateinsightsdirectory.org/document/ember-000163","title":"Greening data centres","publisher":{"name":"Ember","organization":"ember"},"document_type":"report","language":"en","date_published":"2025-05-27","source_url":"https://ember-energy.org/chapter/greening-data-centres/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report examines the energy demands of data centres in ASEAN, particularly those driven by AI, and argues that a dual approach of increasing solar and wind power procurement and enhancing energy efficiency is essential. It highlights that current grid emission targets in key hubs are insufficient and suggests that at least 30% of electricity demand in five ASEAN data centre hubs could be met by wind and solar by 2030 without immediate battery storage. The document emphasizes the critical role of cooling systems in tropical climates and the potential for software optimisation to reduce energy consumption.","ai_generated":true,"unit":"ember-000163#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Current government renewable energy targets for grids serving data centre hotspots are not reducing emission factors rapidly enough to meet sustainability goals. For example, Singapore's grid emission factors are projected to decline by only 4.9% (from 0.48 to 0.45 tCO2e per MWh) between 2019 and 2030, while Indonesia's JAMALI grid is projected to drop 9.4% (from 0.78 to 0.70 tCO2e per MWh).","ai_generated":true,"unit":"ember-000163#insight-1","date_modified":"2026-10-23"},{"text":"Five ASEAN data centre hubs have the potential to meet at least 30% of their 2030 electricity demand using grid-based wind and solar power before battery storage becomes necessary, suggesting that battery costs are not an immediate barrier to adopting these renewables.","ai_generated":true,"unit":"ember-000163#insight-2","date_modified":"2026-10-23"},{"text":"Cooling is a primary driver of energy consumption in data centres, particularly in ASEAN's tropical climate. Cooling alone can account for 39% of total energy use, while computing and servers account for 40%.","ai_generated":true,"unit":"ember-000163#insight-3","date_modified":"2026-10-23"},{"text":"Specific energy efficiency measures can significantly reduce power needs: increasing operating temperature set points by one degree Celsius can save 4.3% to 9.8% of cooling electricity, and immersion cooling technology can reduce power consumption by approximately 40% compared to traditional methods.","ai_generated":true,"unit":"ember-000163#insight-4","date_modified":"2026-10-23"},{"text":"Software optimisation is emerging as a significant lever for efficiency; for instance, the AI assistant DeepSeek is estimated to be around 95% more efficient than traditional AI training methods.","ai_generated":true,"unit":"ember-000163#insight-5","date_modified":"2026-10-23"}],"climate_tags":["solar energy","wind power","energy efficiency","data center","battery energy storage system","Grid decarbonization"],"geography_discussed":["Singapore","Indonesia","Malaysia","Philippines","Thailand","Jabodetabek","Johor","Batam"],"frame_perspective":[],"analysis_type":["policy assessment","technical analysis"]},{"id":"ember-000179","url":"https://climateinsightsdirectory.org/document/ember-000179","title":"Setting the scene","publisher":{"name":"Ember","organization":"ember"},"document_type":"report","language":"en","date_published":"2025-05-27","source_url":"https://ember-energy.org/chapter/setting-the-scene/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report examines the surge in data centre development in Southeast Asia, highlighting how increasing electricity demand—particularly in Malaysia, Indonesia, and the Philippines—threatens climate targets due to reliance on fossil-fuel-dominated grids. It argues that without significant investment in solar and wind energy and improved energy efficiency, the digital boom will lead to a substantial rise in greenhouse gas emissions.","ai_generated":true,"unit":"ember-000179#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The ICT sector is estimated to contribute between 2.1% and 3.9% of global greenhouse gas emissions, with data centres accounting for one-third (360 TWh) of the sector's total electricity use, which exceeded 1,000 TWh in 2023.","ai_generated":true,"unit":"ember-000179#insight-1","date_modified":"2026-10-23"},{"text":"Malaysia is projected to experience the most significant increase in power consumption among the region's hotspots, with demand rising sevenfold from 8.5 TWh in 2024 to 68 TWh by 2030, representing 30% of the country's total national demand.","ai_generated":true,"unit":"ember-000179#insight-2","date_modified":"2026-10-23"},{"text":"Data centre electricity demand is expected to grow sharply in Indonesia and the Philippines by 2030, rising from 6.7 TWh to 26 TWh and from 1.1 TWh to 20 TWh, respectively.","ai_generated":true,"unit":"ember-000179#insight-3","date_modified":"2026-10-23"},{"text":"Emissions from data centre power consumption are projected to surge 14 times in the Philippines, from 0.8 MtCO2e in 2024 to 10.5 MtCO2e by 2030, due to the heavy reliance of the Luzon-Visayas grid on coal.","ai_generated":true,"unit":"ember-000179#insight-4","date_modified":"2026-10-23"},{"text":"To power data centres sustainably and avoid increased fossil fuel dependence, the top five data centre-consuming countries in the region require an estimated $45 to $75 billion in solar and wind capacity investments by 2030.","ai_generated":true,"unit":"ember-000179#insight-5","date_modified":"2026-10-23"},{"text":"While major tech firms like Amazon Web Services, Meta, and Google have global renewable energy targets, progress in Southeast Asia is limited; for instance, only 0.15% of Google's 2.8 TWh electricity consumption in the region came from renewable sources in 2023.","ai_generated":true,"unit":"ember-000179#insight-6","date_modified":"2026-10-23"},{"text":"Singapore has transitioned to a more selective approval process for data centres via the Data Centre-Call For Application (DC-CFA) after a 2019 moratorium, focusing on projects that promote energy efficiency and green power.","ai_generated":true,"unit":"ember-000179#insight-7","date_modified":"2026-10-23"}],"climate_tags":["data center","electric energy consumption","decarbonization","greenhouse gas emissions","solar energy","wind energy","energy efficiency","power purchase agreement"],"geography_discussed":["United States","Johor","Jabodetabek","Batam","Riau Islands","Nordic countries","Europe"],"frame_perspective":[],"analysis_type":["impact assessment","projections"]},{"id":"ember-000384","url":"https://climateinsightsdirectory.org/document/ember-000384","title":"From AI to emissions: Aligning ASEAN’s digital growth with energy transition goals","publisher":{"name":"Ember","organization":"ember"},"document_type":"report","language":"en","date_published":"2025-05-27","source_url":"https://ember-energy.org/app/uploads/2025/05/Report-From-AI-to-emissions-ASEAN.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report highlights that data centres in ASEAN could account for 2% to 30% of national power demand by 2030, risking a significant increase in emissions, particularly in Malaysia, Indonesia, and the Philippines. It argues that approximately 30% of this demand can be met by solar and wind via grids without battery storage. The document advocates for more accessible corporate Power Purchase Agreements (PPAs), national sustainability frameworks, and advanced cooling technologies to ensure the sector's growth does not derail regional decarbonisation targets.","ai_generated":true,"unit":"ember-000384#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Data centre electricity demand is projected to grow unevenly across ASEAN, with Malaysia experiencing the most rapid increase. Malaysia's demand is expected to rise from 9 TWh in 2024 to 68 TWh by 2030, which would represent 30% of its national power consumption.","ai_generated":true,"unit":"ember-000384#insight-1","date_modified":"2026-10-23"},{"text":"The expansion of data centres is expected to cause sharp emission increases in three countries due to fossil-fuel-dependent grids. Malaysia's emissions from data centre power are projected to rise sevenfold from 5.9 MtCO2e in 2024 to 40 MtCO2e by 2030; Indonesia's are expected to quadruple (+13 MtCO2e); and the Philippines' emissions are projected to increase 14 times, from 0.8 MtCO2e in 2024 to 10.5 MtCO2e by 2030.","ai_generated":true,"unit":"ember-000384#insight-2","date_modified":"2026-10-23"},{"text":"A significant portion of the 2030 electricity demand for data centres in the region can be met using renewable energy without immediate reliance on expensive storage. Approximately 30% of this demand can be fulfilled via solar and wind through the grids without needing battery storage.","ai_generated":true,"unit":"ember-000384#insight-3","date_modified":"2026-10-23"},{"text":"To power data centres sustainably and avoid increasing fossil fuel dependence, the top five data centre-consuming countries in the region will require estimated investments of $45 to 75 billion in solar and wind capacity by 2030.","ai_generated":true,"unit":"ember-000384#insight-4","date_modified":"2026-10-23"},{"text":"Energy efficiency, particularly in cooling, is a critical lever for decarbonisation. Cooling can account for 39% of a data centre's total energy consumption. Technologies such as immersion cooling can reduce power consumption by approximately 40% compared to traditional methods.","ai_generated":true,"unit":"ember-000384#insight-5","date_modified":"2026-10-23"},{"text":"Corporate renewable procurement in ASEAN is currently limited, with unbundled Renewable Energy Certificates (RECs) being more dominant than Power Purchase Agreements (PPAs). The report argues that expanding access to virtual PPAs and green tariffs is essential for smaller data centre companies to afford solar and wind supplies.","ai_generated":true,"unit":"ember-000384#insight-6","date_modified":"2026-10-23"}],"climate_tags":["data center","solar energy","wind power","energy efficiency","power purchase agreement","battery energy storage system","Grid decarbonization","carbon credit"],"geography_discussed":["United States","Johor","Jabodetabek","Batam"],"frame_perspective":[],"analysis_type":["impact assessment","policy analysis","projections"]},{"id":"clipolin-001029","url":"https://climateinsightsdirectory.org/document/clipolin-001029","title":"Mengkaji Investasi Iklim Jakarta","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"report","language":"id","date_published":"2021-11","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2021/11/Assessing-Jakartas-Climate-Investments-Bahasa-Indonesian-1.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report finds that Jakarta's climate finance from 2015-2019 was dominated by public funding, totaling USD 44.9 billion across 37 projects, with 83% of this amount committed to the controversial Giant Sea Wall project. Despite having the highest fiscal capacity in Indonesia, Jakarta's environmental spending remained low at 8.6% of its budget in 2017-2018, and private sector investment accounted for only 2% of total climate funding. The document recommends better alignment between Jakarta, the central government, and satellite cities, the implementation of climate budget tagging, and the use of innovative financial instruments like municipal green bonds to mobilize private capital, especially in anticipation of the capital city's relocation.","ai_generated":true,"unit":"clipolin-001029#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Total tracked urban climate funding commitments in Jakarta from 2015 to 2019 amounted to USD 44.9 billion (approximately Rp 652.4 trillion) across 37 projects, with the vast majority allocated to infrastructure.","ai_generated":true,"unit":"clipolin-001029#insight-1","date_modified":"2026-10-23"},{"text":"The Giant Sea Wall (Tanggul Laut Raksasa) project represents a significant anomaly in the data, accounting for 83% (USD 41.2 billion) of total commitments, although it was halted in 2017 due to controversy and lack of adequate environmental and social safeguards.","ai_generated":true,"unit":"clipolin-001029#insight-2","date_modified":"2026-10-23"},{"text":"Public funding dominates Jakarta's climate landscape, with 57% of capital expenditure for climate infrastructure projects funded by the central government. This reflects the city's status as the national capital and a strategic priority for Indonesia's Nationally Determined Contributions (NDC).","ai_generated":true,"unit":"clipolin-001029#insight-3","date_modified":"2026-10-23"},{"text":"Private sector investment is severely underutilized, contributing only 2% (USD 925 million) of total climate funding between 2015 and 2019, with 89% of that amount utilizing balance sheet debt.","ai_generated":true,"unit":"clipolin-001029#insight-4","date_modified":"2026-10-23"},{"text":"Despite having the highest fiscal capacity in Indonesia (score of 6.2), Jakarta's budget allocation for environmental issues was limited to 8.6% of total expenditure in 2017 and 2018.","ai_generated":true,"unit":"clipolin-001029#insight-5","date_modified":"2026-10-23"},{"text":"Jakarta has not accessed loans from financial institutions, including multilateral development banks, between 2017 and 2018, indicating significant untapped room to leverage its fiscal capacity to attract private investment.","ai_generated":true,"unit":"clipolin-001029#insight-6","date_modified":"2026-10-23"},{"text":"There is a lack of alignment in climate priorities between Jakarta and its satellite cities (Bogor, Depok, Tangerang, and Bekasi), which is critical for managing cross-border issues like river flooding and waste management.","ai_generated":true,"unit":"clipolin-001029#insight-7","date_modified":"2026-10-23"}],"climate_tags":["climate finance","climate change adaptation","climate change mitigation","greenhouse gas emissions","sustainable transport","coastal management","waste management","renewable energy","green building","electric vehicle","public–private partnership"],"geography_discussed":["Bogor","Depok","Tangerang","Bekasi","Jabodetabek","East Kalimantan"],"frame_perspective":[],"analysis_type":["financial tracking","policy assessment"]},{"id":"trendas-000109","url":"https://climateinsightsdirectory.org/document/trendas-000109","title":"Jakarta Bukan untuk Semua Orang","publisher":{"name":"Trend Asia","organization":"trend-asia"},"document_type":"report","language":"id","date_published":null,"source_url":"https://trendasia.org/wp-content/uploads/2026/03/Zine-BTH-01_PDF.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report 'Jakarta Bukan untuk Semua Orang' critiques the current state of mobility in Jakarta, where traffic congestion and inadequate public transport create significant financial and health burdens for citizens. It argues that the classification of transportation as a 'non-basic mandatory affair' under Law No. 23 of 2014 leads to budget cuts and a lack of political will. The document advocates for a shift toward integrated, affordable public transport and electric buses, noting that electric bus operational costs in 2024 were approximately 9% lower than diesel buses.","ai_generated":true,"unit":"trendas-000109#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Traffic congestion in the Jabodetabek area results in massive annual losses, including wasted travel time, fuel waste, and increased pollution, with economic losses estimated at hundreds of trillions of rupiah per year.","ai_generated":true,"unit":"trendas-000109#insight-1","date_modified":"2026-10-23"},{"text":"Public transportation is not legally positioned as a basic right in Indonesia; Law No. 23 of 2014 classifies transportation as a 'non-basic mandatory affair' (urusan wajib non-dasar), meaning its provision depends on political will and regional budget priorities rather than minimum service obligations.","ai_generated":true,"unit":"trendas-000109#insight-2","date_modified":"2026-10-23"},{"text":"Regional government fiscal space for public services is shrinking due to cuts in Transfer to Regions (TKD) funds, making public transportation a sector that is easily sacrificed.","ai_generated":true,"unit":"trendas-000109#insight-3","date_modified":"2026-10-23"},{"text":"Electric buses offer a more cost-effective alternative to diesel buses; in 2024, Transjakarta's electric bus operational costs were about 9% cheaper than diesel, while experiences in Medan showed energy cost savings of up to 79%.","ai_generated":true,"unit":"trendas-000109#insight-4","date_modified":"2026-10-23"},{"text":"The lack of adequate public transport disproportionately affects low-income and vulnerable groups, for whom transportation costs are one of the most burdensome components of the cost of living.","ai_generated":true,"unit":"trendas-000109#insight-5","date_modified":"2026-10-23"}],"climate_tags":["public transport","urban transport","air pollution","transport policy","fiscal policy"],"geography_discussed":["Medan","Indonesia"],"frame_perspective":[],"analysis_type":["policy analysis","economic assessment"]}]}