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The Corporate Climate Responsibility Monitor (CCRM) methodology v5.0 provides a stepwise framework for assessing corporate climate claims across four key areas: emissions tracking, target setting, sectoral transitions, and responsibility for ongoing emissions and removals. The 2025 update introduces revised weightings for scoring, a new progress assessment for five-year emission trends, a full methodological revision of sectoral transition evaluations, and updated scientific insights regarding durable carbon dioxide removal.

The Corporate Climate Responsibility Monitor (v5.0) establishes a framework to distinguish genuine corporate climate leadership from greenwashing. It assesses companies across four pillars: comprehensive GHG emissions disclosure (Scopes 1, 2, and 3), the alignment of emission reduction targets with 1.5°C pathways, the implementation of sector-specific transitions, and the scaling of durable carbon dioxide removals (CDR). The guidance emphasizes that net-zero claims are misleading without deep absolute reductions and argues against the use of standalone Renewable Energy Certificates (RECs) and traditional offsetting in favor of 'climate contributions' and millennial-scale durable CDR.

The document introduces a new methodology and a Water Evaluation and Planning System (WEAP) plugin designed to estimate seasonal water stress. By improving the spatial separation of regions, the method aims to prevent the double-counting of freshwater resources and reveal regional disparities in water scarcity that are often hidden by national averages, thereby supporting UN Sustainable Development Goal Target 6.4.

The document provides the technical framework for tracking climate finance in agrifood systems, introducing an expanded taxonomy and a keyword tagging system to capture investments in non-traditional sectors. It distinguishes between 'comparable' and 'adjusted' flows to separate actual investment growth from improvements in data collection. Key data sources include the Global Landscape of Climate Finance (GLCF) and specific agrifood datasets, with a notable increase in finance attributed to energy systems supporting agrifood between 2019/20 and 2021/22.

The TACTS tool provides a framework for stakeholders to calculate solar tariffs using the levelized cost of energy (LCOE) method, evaluate risk reduction and financing instruments, and conduct cost-benefit analyses from the perspective of distribution companies (DISCOMs). It specifically supports the implementation of the Pradhan Mantri Kisan Urja Suraksha Evam Utthaan Mahabhiyan (PM-KUSUM) scheme by quantifying avoided generation, power purchase, and transmission costs against the cost of feed-in tariffs.

The Danger Season 2025 microsite integrates National Weather Service (NWS) alerts, population data, social disadvantage metrics from the Climate & Economic Justice Screening Tool (CEJST), Climate Central’s Climate Shift Index (CSI), and EPA/AirNow’s Air Quality Index (AQI). The methodology focuses on the period from May to October, identifying counties under extreme weather alerts or experiencing unhealthy air quality. It calculates four daily indicators: the total population facing alerts, the percentage of disadvantaged people affected, the percentage of the population facing at least one alert, and the proportion of extreme heat alerts attributable to climate change. The scope includes the contiguous United States, Alaska, Hawai'i, Puerto Rico, and the U.S. Virgin Islands, though certain datasets like CSI and AQI have specific geographic gaps.

The Clean Air Task Force (CATF) developed an in-house methodology to model the impact of the Advanced Clean Trucks (ACT) rule on diesel emissions and public health. By layering ACT's zero-emission vehicle (ZEV) sales mandates onto U.S. EPA emissions projections for 2032 and 2038, the model estimates avoided diesel fuel consumption and subsequent pollutant reductions. The analysis considers three scenarios: current adoption (11 states), expanded adoption (20 states), and full adoption across 48 contiguous states. To determine health impacts, the model uses the EPA's CO-Benefits Risk Assessment (COBRA) screening model to translate emission reductions into lives saved. For example, the model estimates that ACT enforcement in California in 2038 would reduce on-road diesel use by 547,681 gallons, representing a 16% reduction compared to a business-as-usual case, which would save 94 lives.

The Clean Air Task Force (CATF) utilizes the U.S. EPA's CO-Benefits Risk Assessment (COBRA) screening model to estimate health impacts from 2026 diesel emissions. The methodology employs a damage function approach to translate emissions into ambient PM2.5 concentrations, then into adverse health effects such as premature mortality, and finally into monetized economic damages. For 2026, national attributable premature mortality is estimated to range from 3,700 to 8,500 deaths. Additionally, CATF calculates cancer risk using a California Air Resources Board (CARB) risk factor, estimating 220 lifetime cancers per million population for 2026 based on projected concentrations of 0.25 ug/m3.

The report outlines a systematic approach to estimating top-down climate finance needs, distinguishing them from bottom-up needs derived from Nationally Determined Contributions (NDCs). CPI's methodology involves collecting data from nearly 100 reports, standardizing sector classifications using its Global Landscape of Climate Finance (GLCF) taxonomy, and harmonizing timeframes, currencies, and value types. The document emphasizes that annual climate finance flows must increase significantly, reaching USD 7.5 trillion per year by 2030 and over USD 8.8 trillion per year from 2031 to 2050. It also addresses data gaps in sectors like aviation and wastewater, the inclusion of non-climate solutions like fossil fuel deployment, and the necessity of redirecting capital from high-carbon activities to meet net-zero targets.

The document outlines a four-step process for calculating the carbon footprint of salmon, covering feed production, farming, processing and packaging, and transportation. It details how data on waste, electricity, fuel, and packaging are converted into CO2 equivalents to identify mitigation opportunities and track progress toward the "The Salmon of 2030" benchmark.

The document outlines the technical approach for modeling the 'Current Policies' and 'IRA Repeal' scenarios using the Energy Policy Simulator (EPS). It details which specific IRA sections—including tax credits for renewable energy, electric vehicles, and carbon capture—were included in the analysis, which were omitted as 'out of scope,' and the specific assumptions used to calculate their effects on emissions and energy demand.

The EU Green Policy Tracker prototype assesses the implementation of four specific European Green Deal (EGD) policies in Sweden and Estonia. Using a combination of desk research and semi-structured interviews with 12 government officials, the methodology employs a standardized taxonomy to identify facilitating and hindering factors. Implementation progress is categorized into initial (red), intermediate (amber), and advanced (green) stages based on the percentage of expected actions completed, which are then aggregated into an overall implementation score for each country.

The CoMAT Methodology guide details how the tool calculates methane emissions using a bottom-up equipment-based inventory combined with specific top-down measurements. It outlines the data inputs, emission factors, and abatement strategies for various oil and gas industry segments, including exploration, production, processing, transmission, storage, LNG, and distribution. The tool leverages defaults primarily from the US GHG Inventory (US GHGI) while allowing for country-specific updates to refine emissions inventories and design policy strategies.

The report establishes a comprehensive framework for tracking sustainable agriculture finance in India, adopting a value-chain approach that covers upstream, farming, and downstream activities. It defines the criteria for 'sustainable agriculture' based on food security, emission reduction, and climate resilience, and details the data sources used—including government budgets, OECD databases, and private equity trackers—to identify public and private disbursements.

The Climate Bonds Initiative (CBI) has established a methodology for its Social and Sustainability Bond Dataset (SSBD) to ensure the credibility of social and sustainability bonds. The framework requires that 100% of net proceeds be used for social or environmental projects, with at least 90% meeting specific screening criteria. Bonds are classified as 'aligned', 'non-aligned', or 'pending' based on their use of proceeds (UoP), disclosure transparency, and adherence to minimum safeguards. The methodology integrates ICMA principles and UN Sustainable Development Goals (SDGs) to categorize projects across sectors such as education, healthcare, and renewable energy, while explicitly excluding fossil fuels and weapons.

The Climate Bonds Initiative's methodology for the Social and Sustainability Bond Dataset (SSBD) establishes a rigorous screening process to identify credible social and sustainability bonds. To be included, instruments must be self-labelled debt, provide adequate public disclosure, and allocate 100% of net proceeds to social or environmental projects, with at least 90% meeting specific eligibility criteria. The framework emphasizes ex-ante impact confirmation for target populations and employs a strict list of absolute exclusions, including fossil fuel exploration and weapons production. Bonds are classified as aligned, non-aligned, or pending based on their adherence to these standards, with a two-year lookback period used for complex assessments.

The appendix outlines the technical process for estimating the 'government plans and projections' (GPP) pathway using data from 19 major producer countries, which accounted for approximately 81% of global fossil fuel production in 2022. It describes the harmonization of diverse national data into exajoules (EJ) per year and the use of IEA's Stated Policies Scenario (STEPS) to scale these figures to a global estimate. The document also explains the conversion of energy units into physical units and extraction-based greenhouse gas emissions using specific emission factors for coal, oil, and gas.

The Climate Policy Initiative (CPI) has introduced a methodology framework for developing Climate Finance Roadmaps to address a global climate investment gap estimated at USD 6.1 trillion per year by 2030. The framework is designed to identify suitable investors, necessary financial instruments, and regulatory measures to mobilize climate finance at scale. CPI intends to test this approach in pilot geographies and sectors and invites external stakeholders to adopt the framework or provide feedback to refine the living methodology.

The report details a comprehensive methodology for mapping green finance in India, defining the scope of 'green finance' to include climate finance and environmental objectives like biodiversity and resource conservation. It establishes a framework for categorizing financial flows by source (domestic/international, public/private), instrument (grants, debt, equity), and sector (clean energy, energy efficiency, clean transportation, and climate adaptation). The methodology employs a variety of data sources, including government budgets, OECD CRS, and project-level databases, while applying specific assumptions such as a 70:30 debt-to-equity gearing ratio and the use of Rio Markers for international public finance. A significant portion of the document is dedicated to the granular classification of on-farm agricultural adaptation activities, categorizing government schemes into 'absolute', 'lower bound', and 'upper bound' based on their adaptation relevance.

This report describes the methodology used by the Climate Policy Initiative (CPI) to quantify and compare financial flows for land use with climate action components in Brazil for the period 2021-2023. It details the criteria for classifying finance into mitigation, adaptation, dual benefits, and loss and damage, while outlining the data sources and the 'Climate Finance Ecosystem' used to track public and private resources.