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The document outlines the technical structure and legal permissions for the Climate TRACE Inventory (v5.11.0). It defines the metadata for emissions source, country-level, confidence, and ownership files, while specifying that most data is available under the Creative Commons Attribution 4.0 International Public License. It also provides a comprehensive list of recommended citations for various sectors and identifies third-party data sources used for specific emissions estimates.

The analysis finds that if approximately 2,430 large companies (consuming over 100 GWh/year) adopted the RAcc model, the resulting demand would cover about 66% of global commercial and industrial electricity consumption and avoid 5.5 billion tCO2e annually. The report identifies a tipping point where adoption by the top 20% of these companies (~539 organizations) would exceed existing global renewable energy supply, necessitating the construction of new renewable generation capacity.

The document describes how replacing diesel-powered mining machinery with battery-electric alternatives or trolley-assist systems reduces greenhouse gas emissions. It focuses on the Copper Mountain Mine, where the use of hydroelectricity-powered trolley-assist systems for haul trucks is expected to reduce annual emissions by approximately 9,400 tCO2e.

The document highlights the use of methane drainage and utilization systems at the Pniówek Coal Mine in Poland to reduce greenhouse gas emissions. By capturing methane from coal seams and using it for on-site power or heat, the mine converts high-global warming potential methane into CO2. This specific project is estimated to reduce emissions by over 110,000 tonnes of CO2e per year, with a broader global potential for such solutions estimated at 833 MtCO2e.

The document highlights the transition to electric vehicles (EVs) as a method to eliminate tailpipe emissions, citing Shenzhen's replacement of internal combustion engine buses with 16,000 electric buses. While the transition in Shenzhen reduced transportation emissions by an estimated 1.4 million tonnes CO2e annually, it also increased emissions within the electricity sector due to charging demand. The report notes a total project impact of 1 MtCO2e and a global emissions reduction potential for EV transitions of 3 BtCO2e.

The document highlights the impact of Thailand's NAMA Rice Farms program, which utilizes Alternate Wetting and Drying (AWD) and balanced fertilizer use to reduce methane and nitrous oxide emissions in rice cultivation. The program has achieved a reduction of 1.9 million tonnes of CO2e between 2018 and 2024, with a current annual project impact of 266,730 tCO2e across 320,000 hectares.

The document highlights Uganda's use of the United Nations-backed REDD+ initiative to combat deforestation, which saw the country lose over 60% of its forests between 1990 and 2015. By implementing improved forest monitoring, community-led reforestation, and energy-efficient stoves, Uganda achieved a verified emissions reduction of 8 million tonnes CO2e between 2016 and 2017. This success made Uganda the first African country to receive results-based payments from the Green Climate Fund, totaling 31 million USD. The specific project spotlighted has an estimated annual emissions reduction potential of 4 MtCO2e.

The document highlights the Amazon solar farm in Rajasthan, India, which has 210MW of capacity and avoids an estimated 280,000 tonnes of CO2e annually by providing zero-carbon electricity to a carbon-intensive grid. It argues that expanding renewable energy in coal-reliant systems is a highly effective way to reduce power-sector emissions and improve air quality.

The document examines how electrifying heating systems and improving energy efficiency in buildings can reduce urban emissions, highlighting Copenhagen's achievement of reducing building-related emissions by over 60% between 2019 and 2023. It notes that while such measures reduce emissions at the source, they can increase induced emissions if the electricity grid remains carbon-intensive.

The Glenbrook Steel Mill in Auckland, New Zealand, plans to install an electric arc furnace (EAF) by 2026 to replace half of its coal-based ironmaking. Supported by a $300 million investment and GIDI co-funding, the project will use a 30 MW renewable-energy agreement with Contact Energy to leverage New Zealand's approximately 90% renewable grid. This transition is expected to reduce the mill's annual emissions by up to 1 million tonnes of CO2e.

The Jardim Gramacho project in Rio de Janeiro, managed by COMLURB, has transitioned from being Latin America's largest landfill to a climate mitigation site. By implementing a landfill-gas capture system and large-scale mangrove restoration along Guanabara Bay, the project avoids an estimated 850,000 tonnes of CO2e annually. The document highlights that while conventional landfill closure is often mistaken for mitigation, active systems that capture methane for combustion or energy use, combined with biocovers and vegetation restoration, can effectively curb emissions from legacy waste sites.

The document highlights the use of soil activators and organic substitutes to reduce synthetic nitrogen fertilizer application by up to 20% without compromising crop yields, noting a specific project impact of 12,765 tCO2e in North America.

The document describes how a global automaker used Climate TRACE and TASA Analytics data to move beyond coarse 'spend-based' emissions factors to granular, facility-level intelligence for steel and aluminium. By integrating Scope 1 and 2 emissions factors with rapid IO-LCA (rLCA) models, the project revealed significant emissions intensity variations across production methods and countries. Key findings highlight the potential for emissions reductions through increased scrap use in both steel and aluminium production and the inaccuracy of standard EEIO data in certain regions.

The document describes remote sensing as the process of gathering information from a distance by detecting electromagnetic waves. It distinguishes between active sensing, which transmits signals to measure reflections, and passive sensing, which measures naturally emitted or reflected waves. Remote sensors can be space-based, aerial-based, or ground-based, though Climate TRACE primarily utilizes satellite-based sensors for their global coverage. The effectiveness of satellite remote sensing is determined by spectral resolution (wavelength bands), spatial resolution (pixel detail), and temporal resolution (revisit frequency). Climate TRACE integrates this data with satellite imagery and ground truth data to monitor greenhouse gas emissions from various sources and train AI/ML algorithms.

The document provides a step-by-step guide for users to identify all owners of a high-emitting asset, using the Troll oil and gas field in Norway as a case study. It clarifies that while the website dashboard displays only the primary owner, the CSV files provide a full list of owners and their respective percentage stakes.

The document outlines the structure and access requirements for the Climate TRACE public dataset on Google BigQuery, including a detailed data catalog of emissions, metadata, and sector-specific tables. It provides step-by-step instructions for querying the data, managing permissions, and exporting results via CSV, JSON, or Parquet formats, while noting that query costs are borne by the user.

Climate TRACE estimates that anthropogenic methane emissions in 2025 were just over 410 million tonnes, with agriculture, fossil energy, and waste accounting for 97% of the total. The report argues that slashing methane is the most impactful way to keep global warming under 2 degrees Celsius due to the gas's powerful near-term warming effect. It identifies specific actionable opportunities: reducing methane intensity in oil and gas production (particularly in the US and Mexico), capturing coal mine methane, targeting a small number of high-emitting landfills, and addressing enteric fermentation and rice cultivation in agriculture.

The STARRS pilot project, initiated by Climate Group and Climate TRACE, demonstrates how satellite imagery and artificial intelligence can provide timely, granular greenhouse gas (GHG) emissions data for subnational governments. By tracking six pilot regions—Abruzzo (Italy), Basque Country (Spain), Jalisco (Mexico), Querétaro (Mexico), Pernambuco (Brazil), and Western Cape (South Africa)—the project addressed common barriers to emissions accounting, such as high costs and long timeframes associated with traditional bottom-up methods. The project provided historical data from 2015 to 2021 across sectors including electricity, heavy industry, and road transport, while also mapping biomass changes. Findings for the pilot regions highlighted specific emission drivers, such as the dominance of the Bilbao Refinery in the Basque Country's oil and gas sector and the significant impact of feedlots in Jalisco and Western Cape.