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The SHIFT Calculator estimates induced travel—the increase in vehicle miles traveled (VMT) following road capacity expansions—using empirical elasticities. It applies a 1.0 ratio for interstate highways and 0.75 for other freeways and arterials, predicting that a 1% increase in lane mileage leads to a corresponding increase in VMT over 5 to 10 years. The tool also calculates cumulative greenhouse gas emissions through 2050 based on two scenarios: a business-as-usual case and one aligned with the US Nationally Determined Commitment (NDC), which assumes 100% electrification of new passenger vehicles by 2035.

The Mini-Grid Emissions Tool, developed by Sustainable Energy for All (SEforALL), addresses the lack of standardized carbon tracking in the mini-grid sector. Unlike previous methods that rely on a single default emissions factor and total energy generated, this tool calculates emissions avoided based on actual energy consumed and the diverse range of previous energy sources used by customers. It incorporates specific data for different household energy access tiers, kerosene lamp types, and fossil fuel generator efficiencies to provide a more accurate estimate of climatic benefits.

The document outlines the methodology for the Klimatkalkylatorn tool, which estimates a user's climate footprint across four consumption categories: housing, food, transport, and shopping, plus a fixed societal impact. It details the use of Swedish national statistics (SCB), the GTAP input-output model for indirect emissions, and specific emission factors for energy and transport. The tool compares individual results against a Swedish average of 10.7 tonnes CO2e, a global average of 6.4 tonnes CO2e, and a 2020 target of 7 tonnes CO2e per person.

The document details a methodology for assessing 'embedded' water risk in global trade by combining the IOTA hybrid MRIO model with water stress data from the World Resources Institute's Aqueduct database. It explains how production of agricultural commodities is linked to final consumers and how country-level water risk is calculated using two distinct indicators: aggregate national water stress and the proportion of land area under stress. The methodology is illustrated through examples of maize and rice consumption, showing that regions like south and central Asia face high consumption-based water risk. Future improvements aim to increase spatial resolution to the sub-country level and expand the range of risk indicators to include groundwater scarcity and flood likelihood.

The document details the technical approach for estimating the economic and environmental impacts of fuel efficiency standards. It specifies the use of updated census data, regional energy projections, and specific emissions derivation methods for cities and states.

The document provides the technical basis for estimating EV charging emissions and costs in the US. It explains the use of average emissions intensity based on EPA eGRID data, adjusted for transmission losses and upstream feedstock emissions. It also describes a modified Oak Ridge Competitive Electricity Dispatch (ORCED) model used for hourly emissions estimates. Additionally, it outlines the process for calculating residential charging costs across 50 US cities, accounting for tiered rates, time-of-use (TOU) plans, and specific utility data.

The document outlines a technical framework for calculating fuel use across various truck types—including tractor-trailers, straight trucks, and cargo vans—using data from the Freight Analysis Framework (FAF) and the Vehicle Inventory and Use Survey (VIUS). It establishes baseline fuel economies (e.g., 5.8 mpg for tractor-trailers) and projects improvements by 2025 based on technology packages such as aerodynamic devices and hybrid-electric powertrains. Additionally, it applies these methodologies to estimate the current fuel use and future savings for the fleets of UPS, FedEx, PepsiCo, The Coca-Cola Company, and Walmart.

The document details the construction of the EW3 database, which integrates 2008 Energy Information Administration (EIA) data with NREL and Argonne National Laboratory water coefficients to estimate freshwater withdrawals and consumption. It describes the process of mapping cooling systems to specific generators, using Google Earth to verify cooling types, and applying the Water Supply Stress Index (WaSSI) to identify watersheds where electricity generation significantly increases water stress. The methodology also covers the projection of water use through 2036 using the Regional Energy Deployment System (ReEDS) model and the calculation of water and carbon intensities for the top 15 U.S. electricity providers.

The document details the selection process and scoring criteria used to evaluate 30 companies' palm oil commitments. Companies were selected from the Forbes Global 2000 (2013) and QSR Magazine’s Global 30 (2012) lists. Scoring was based on public data available as of January 16, 2014, and evaluated across five categories: deforestation-free commitments, peat-free commitments, traceability, transparency, and early action. Each category is worth 20 points, with specific rubrics for awarding points based on the strength and specificity of company commitments and reporting.

The document outlines the technical approach for estimating economy-wide GHG emissions for countries and the global aggregate, assuming full achievement of NDC targets. It explains the use of supplemental data for sectors or gases not covered by NDCs and the inclusion of emissions like international bunkers to determine global trajectories. These estimates are used by the Climate Watch NDC Tracker to track progress and identify gaps in global emissions pathways.

The document outlines the methodology for the State Overview resource developed by the World Resources Institute as part of the American Cities Climate Challenge: Renewables Accelerator. This resource is designed to help U.S. cities understand regulatory frameworks and renewable electricity procurement options through dedicated webpages for all 50 states and the District of Columbia.

The document describes the construction of the Aqueduct Water Risk Atlas, which uses a composite index approach to map 12 water-risk indicators globally. Six indicators were generated using a combination of time series estimators, spatial regression, and a sparse hydrological model, while the other six were adapted from existing publications. The authors note that model accuracy is primarily constrained by the lack of public data on major infrastructure, in-situ water quality, and river gauge measurements, and that overall index scores cannot be validated due to a lack of public datasets on water-related losses.

The document outlines the technical framework and curation methodology for the American Cities Climate Challenge: Renewables Accelerator website, a collaborative resource by the World Resources Institute and Rocky Mountain Institute designed to support city sustainability staff in the procurement of renewable energy.

The document outlines the methodology for the Climate Finance Requirements Tracker, a tool that systematically tracks quantitative climate finance data from all rounds of nationally determined contributions (NDCs). Since 2021, the World Resources Institute has used this process to distinguish between international and domestic funding requirements for mitigation and adaptation, while also compiling data on the economic impacts of climate-related loss and damage.

The document presents a framework for aggregating localized water-risk scores into national and river basin-level rankings to support administrative decision-making and financial portfolio evaluation. It focuses on five objective physical indicators: baseline water stress, inter-annual variability, seasonal variability, flood occurrence (1985-2011), and drought severity (1901-2008). The rankings exclude subjective factors such as water governance, investment, or conservation efforts.

The document outlines an effort to make complex global climate data more accessible by converting it into simple indicators and open geospatial formats. This process aims to reduce barriers for users who need to anticipate trends in agriculture, energy demand, disaster risk, and water management to inform adaptation strategies. The resulting data are hosted on PREPdata and Resource Watch, with the source code available on GitHub.

The document outlines a technical approach to determine the extent of NDC enhancement by comparing estimated target-year greenhouse gas emissions under a Party's previous NDC against those under its subsequent NDC. The method covers both NDCs with explicit GHG reduction targets and those based on non-GHG targets and policies.

The World Resources Institute, in partnership with the World Cocoa Foundation and Climate Focus, developed two tools to support deforestation-free cocoa commitments in West Africa. The West Africa Cocoa Dataset aggregates data from 19 companies, identifying 840,000 unique plots covering approximately 1.5 million hectares. To protect farmer privacy, this dataset is shared as a heat map rather than raw plot data. The Cocoa Deforestation Risk Assessment provides a harmonized method to prioritize deforestation prevention; it found that recent forest loss significantly influences risk levels, while legal protections in areas like Taï National Park and Bia National Park correlate with lower priority rankings due to a lack of recent loss.

The document introduces the 'Forest Footprint for Cities' methodology, which connects city-level consumption and international trade to global tropical and subtropical deforestation. By quantifying the hectares of forest lost and the resulting CO2 emissions embodied in urban products, the method aims to make the external impacts of city governance and sustainability planning visible, enabling cities to join national and private sector efforts in reducing deforestation.

The Climate Watch Country Greenhouse Gas Emissions Data provides comprehensive, comparable GHG emissions data for 193 countries and the European Union from 1990 onwards, covering all GHG types and sectors including energy, industrial processes, agriculture, waste, and LULUCF. The dataset typically operates with a three-year reporting lag, such as reporting 2020 data in 2023, and aims to help countries identify mitigation opportunities and compare emission profiles.