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The RES Tracker methodology describes the process of identifying national renewable energy targets for 2030, categorising them by source reliability, and addressing specific data challenges regarding solar capacity reporting and the climate impact of bioenergy.

The document outlines the technical framework for the State of Climate Action series, focusing on tracking global greenhouse gas emission reductions and carbon removal. It details the process of translating sectoral transformations into actionable targets and the categorization of progress (e.g., 'on track' or 'off track'). The 2024 update introduces 2035 targets for 16 indicators, a new indicator for wind and solar power in electricity generation, and revised transport sector targets based on recent modeling.

The report details a systematic approach to quantifying 'bottom-up' climate finance needs—the capital countries state they require to meet national targets—as opposed to 'top-down' predictive models. CPI reviewed 168 NDCs, standardizing diverse data on currency, timeframes, and sector classifications using its Global Landscape of Climate Finance (GLCF) taxonomy. The methodology distinguishes between unconditional (domestic) and conditional (international) needs, while acknowledging significant data gaps, as less than half of the reviewed NDCs provided fully costed finance needs.

The guide establishes 'Common Principles' for tracking green finance, emphasizing conservativeness and granularity. It details a three-step qualification process for adaptation finance and a whitelist-based approach for mitigation. It also introduces a methodology for biodiversity finance based on OECD Rio Markers and the Kunming-Montreal Global Biodiversity Framework, while addressing challenges like taxonomy misalignment and resource limitations within development finance institutions.

The methodology for the Landscape of Climate Finance in Africa 2024 describes the framework used to identify and categorize climate finance flows. It employs a taxonomy to distinguish between mitigation, adaptation, and dual-benefits finance across sectors such as energy, transport, and agriculture. The approach relies on a mix of public and proprietary data from sources like the OECD, BNEF, and the World Bank, while acknowledging significant gaps in domestic public expenditure tracking and private sector reporting. The document also details the classification of African countries by subregion and income status.

The report proposes a two-step assessment approach to link financial institutions' net zero strategies to real-world impacts. It emphasizes tracking investments in new assets rather than existing portfolios to avoid the 'divestment' loophole where assets are transferred without reducing emissions. The methodology uses a multi-level ownership tree (up to Level 2) to attribute finance to indirect investors based on equity and debt weightings, utilizing data from sources like Bloomberg Terminal and CPI's Global Landscape of Climate Finance.

The methodology employs Functional Urban Areas (FUAs) to define urban scope and tracks primary capital flows for mitigation and adaptation. It combines project-level data from sources like the OECD-DAC and BNEF with capital expenditure estimations for transport, buildings, and energy systems. Needs assessments are derived from top-down global models, adjusted by regional urban population shares and sector-specific inclusion criteria.

The document details the technical approach for mapping disruptive flooding and its impact on critical infrastructure across US territories. It describes the use of NOAA tide gauge data, digital elevation models, and three sea level rise scenarios (low, medium, and high) to project inundation. The analysis overlays these flood maps with datasets covering housing, education, industrial sites, energy, government, and health facilities, while incorporating socioeconomic data from the White House Council on Environmental Quality to assess impacts on disadvantaged communities.

The report outlines the technical process of combining Fathom's Global Flood Map (v3.1) with Public Safety Canada's residential building data and probabilistic vulnerability functions. It describes the use of 'big data' from US FEMA insurance claims to model damage distributions across 10 residential building types. The methodology accounts for flood defenses based on urbanization levels and applies the trapezium rule across eight return periods to estimate economic losses. Results show that Canada's defended AAL is projected to increase from 1,423 million CAD in 2020 to 1,681 million CAD by 2050, while undefended AAL is significantly higher, reaching 5,050 million CAD by 2050.

The Union of Concerned Scientists analyzed US Senate lobbying disclosure reports from January 2019 to December 2023 to quantify corporate influence on the food and farm bill. The analysis found that giant agribusiness companies and industry associations spent over half a billion dollars during this period to influence legislation. The methodology involved searching the Senate database for the phrase "farm bill," cleaning duplicate data, accounting for report amendments and terminations, and categorizing entities into sectors such as Agribusiness, Fuel/Energy, and Pharmaceuticals to assess the scale of corporate profit prioritization in federal farm policy.

The Green Bond Dataset (GBD) methodology establishes a science-based framework for screening self-labelled green debt instruments. To be included in the 'Aligned' list, a debt instrument must be self-labelled, have adequate public disclosure, and allocate 100% of net proceeds to green assets, with at least 90% meeting specific eligibility criteria. The methodology employs a three-step screening process: identification and pre-requisite checks, screening of green credentials against sector-specific definitions, and evaluation of the use of proceeds (UoP) threshold. Absolute exclusions apply to fossil fuel exploration, production, refining, and fossil fuel-based heat, cool, and electricity generation, regardless of the percentage of proceeds. The GBD allows for a 'margin of flexibility' of up to 10% for assets where alignment is uncertain or metrics are unavailable, and utilizes a two-year lookback period for complex expenditure assessments. While external reviews are recommended, they are not mandatory for GBD inclusion if equivalent information is disclosed. The document also distinguishes the GBD from the Climate Bonds Standard Certification scheme, noting that GBD inclusion is based on post-issuance screening of public data, whereas Certification is a voluntary pre-issuance application process.

The guide establishes a methodology for assessing corporate climate responsibility across four key areas: emissions tracking and disclosure, target setting, emission reduction measures, and responsibility for unabated and residual emissions. It emphasizes alignment with 1.5°C-compatible pathways, the necessity of covering all emission scopes (including Scope 3), and the distinction between genuine emission reductions and misleading offsetting or 'insetting' claims. The document provides specific benchmarks for various industrial sectors and detailed criteria for high-integrity renewable electricity procurement and carbon dioxide removal (CDR) strategies.

The methodology focuses on indicators with a 2030 horizon to align with the Paris Agreement's 1.5°C goal. It evaluates companies across five main dimensions: current energy production (using a fossil fuel equivalence method to compare renewables and fossil fuels), cash-flow allocation (analyzing CAPEX for exploration versus low-carbon solutions), fossil fuel strategy (assessing upstream expansion and production overshoot relative to the IEA Net Zero Emissions scenario), diversification strategy (projecting 2030 energy mixes), and emission targets (calculating carbon intensity excess and reliance on CCUS and offsets). The analysis covers 6 European companies (BP, Eni, Equinor, Repsol, Shell, TotalEnergies), 2 US companies (Chevron, ExxonMobil), and 4 National Oil Companies (ADNOC, Petrobras, QatarEnergy, Saudi Aramco).

The Global Subnational Agricultural Production (GSAP) database is the first standardized global dataset providing subnational agricultural production data (2010–21) for the world's 50 most relevant crops. By collecting data from national agricultural censuses and surveys at the district, province, or region level, GSAP fills a critical information gap left by national-level data sources like FAOSTAT. The database currently covers 185 countries and approximately 15,000 subnational jurisdictions, capturing a significant portion of global production for staples such as soybean (92%), maize and sugarcane (85%), and wheat and rice (75%). The project aims to enhance the accuracy of analyses regarding yield gaps, climate adaptation, and supply chain sustainability, with future goals including the launch of a public online platform and the expansion of data to include livestock and forestry.

The report details a methodology for assessing nitrogen movement through supply chains using UK trade data from 2017-2021 and UN Food and Agriculture Organization statistics. It identifies the top five agricultural and aquatic imports and exports by nitrogen mass and suggests expanding future research to include chemical and forestry commodities and country-specific flows.

The document outlines the methodology used by the International Institute for Sustainable Development (IISD) to map public financial flows in India's energy sector. It defines government support as encompassing subsidies, state-owned enterprise investments, and lending by public financial institutions. The annex introduces new subsidies for green hydrogen, battery storage, and electric vehicles, while retrospectively revising methodologies for coal and renewable energy support. It also details the tracking of government receipts from coal, oil, gas, and renewables to provide a comprehensive view of the financial relationship between the state and the energy sector.

The document outlines the technical framework for assessing electric vehicle (EV) benefits, utilizing EPA eGRID data for power plant emissions and the GREET model for upstream feedstock emissions. It specifies the use of a sales-weighted EV efficiency of 0.314 kWh/mile and an average annual mileage of 11,599 miles. Public health benefits are derived from the American Lung Association's use of the EPA COBRA model, while economic data includes announced manufacturing jobs from the EV Jobs Hub and charging infrastructure growth from the Alternative Fuels Data Center. Fuel cost comparisons rely on NREL utility rates and GasBuddy gasoline prices.

The guide outlines how to detect greenwashing by analyzing emissions data, target setting, and the use of controversial technologies. It emphasizes the importance of absolute emissions over intensity targets and warns against the over-reliance on carbon offsets, natural gas, and unproven carbon removal technologies.

The 2024 Toll from Coal analysis uses the U.S. EPA's COBRA v5.2 model to link emissions of PM2.5, SO2, NOx, and VOC from coal-fired power plants to health outcomes and economic damages across the continental United States. Comparing 2024 data to 2019, the analysis finds that reported NOx and SO2 emissions fell by more than one-third, while direct PM2.5 and VOC emissions decreased by one-quarter. These emission reductions are associated with a decline in all-cause mortality from PM2.5 exposure (from 6,700 to 5,100 deaths) and non-fatal heart attacks (from 2,750 to 1,670). However, ozone exposure was still associated with nearly 1,500 deaths in 2024. Total health damages in 2024 were valued at $100 billion in 2023 dollars.

The Climate Bonds Resilience Taxonomy (CBRT) Methodology establishes a science-based framework to scale private and public financing for climate adaptation and resilience. It categorises investments into four types—adapting measures, adapted activities, enabling measures, and enabling activities—across seven thematic areas including Resilient Infrastructure and Resilient Natural Systems. The methodology employs a tiered screening process to ensure a "measurable reduction in vulnerability (or exposure)" while managing maladaptation risks and ensuring no significant harm to climate mitigation. The framework is designed for global applicability and interoperability with existing standards like the EU Sustainable Finance Taxonomy and the MDB Joint Methodology.