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The document outlines the methodology and data used to analyze pesticide application rates and heat index exposure for farmworkers in the US. It details the use of USGS and NASS data to identify high-risk pesticides and calculate heat index days, providing specific state-level and county-level data for California, Florida, and Washington.

The paper develops a methodology to estimate fuel economy in sub-Saharan African cities, specifically Nairobi, by collecting data on both formal and informal vehicle fleets. Using general linear modelling (GLM) and artificial neural networks (ANN), the study found that fuel economy for bodabodas, tuktuks, passenger cars, and matatus in Nairobi is 2–3 times worse than in their countries of import. The GLM was identified as the more effective model for predicting fuel economy based on vehicle characteristics.

The Union of Concerned Scientists utilized the InMAP (Intervention Model for Air Pollution) to estimate average annual concentrations of PM2.5 in California at a resolution of one square kilometer. By mapping these concentrations to census block groups and integrating data from the 2012–2016 American Community Survey, the study aimed to determine population-weighted exposure by demographic group. The authors justify the use of the reduced-complexity InMAP model over conventional chemical transport models (CTMs) by noting its superior performance on population-weighted metrics and its ability to provide the fine spatial resolution necessary to analyze exposure equity in racially or economically segregated urban areas.

The document details the operational framework for the 2019 Global Landscape of Climate Finance, defining climate finance as resources aimed at reducing emissions, enhancing greenhouse gas sinks, and increasing resilience to climate impacts. It establishes a standardized accounting methodology to avoid double counting and ensure data consistency across public and private sectors. The methodology prioritizes primary capital flows and financial commitments over disbursements, excluding secondary market transactions and investments that risk carbon lock-in. It provides a comprehensive sectoral breakdown for mitigation (e.g., renewable energy, energy efficiency, low-carbon transport) and adaptation (e.g., water management, coastal protection), and defines the geographic classification of countries into OECD and non-OECD regions.

The document outlines a framework for facilitating peer learning among adaptation policy-makers to move away from passive, presentation-heavy meetings toward interactive knowledge exchange. It details seven core planning principles—purpose, context, people, power, place, process, and monitoring—and provides specific methodologies for technical, relational, and reflective interaction, such as 'Knowledge Clinics' and 'Participatory Timelines'. These methods were tested across seven Thematic Issue Forums involving government representatives from 23 countries to accelerate the development and implementation of National Adaptation Plans.

The Union of Concerned Scientists (UCS) developed a methodology to assess eight major investor-owned oil, gas, and coal companies on their climate responsibility. The assessment uses 28 metrics across four broad areas: renouncing disinformation, planning for a carbon-free world, supporting effective climate policies, and disclosing climate risks. Companies are scored on a five-point scale from 'advanced' to 'egregious' based on publicly available data from July 1, 2016, to June 30, 2018.

The Climate Bonds Initiative (CBI) employs a three-step screening process to identify and validate green bonds and loans for its database. This involves identifying self-labeled green instruments, verifying alignment with the Climate Bonds Taxonomy across eight sectors, and ensuring at least 95% of proceeds are allocated to eligible green assets. The methodology explicitly excludes fossil fuel energy and projects that extend the life of fossil fuel assets. Instruments are categorized as included, pending, or excluded, with a mechanism for reclassification based on new data or updated scientific criteria.

The Climate Bonds Initiative (CBI) employs a three-step screening process to identify eligible green bonds and loans for its database: identifying green-labelled bonds, screening assets against the Climate Bonds Taxonomy, and evaluating the allocation of proceeds. To be included, a bond must allocate at least 95% of its proceeds to aligned green assets; any bond where more than 5% of proceeds are used for working capital, social projects, or non-aligned assets is excluded. The methodology explicitly excludes fossil fuel energy and any assets that extend the life of fossil fuel usage, such as 'clean coal'. The Climate Bonds Taxonomy covers eight categories: energy, transport, buildings, water management, waste management & pollution control, nature-based assets, industry & energy-intensive commercial, and information technology & communications (ICT).

The document outlines the quantitative scoring system used to translate qualitative likelihood and confidence levels from the Climate Science Special Report (CSSR) and the IPCC Fifth Assessment Report (AR5) into a visual guide for extreme weather attribution in the continental United States.

The Union of Concerned Scientists used a combination of NOAA elevation data, tide gauge records, and Zillow's ZTRAX database to identify coastal properties at risk of chronic inundation. The analysis defines chronic inundation as areas flooded at least 26 times per year and evaluates three sea-level-rise scenarios: high (6.6 feet), intermediate (4.0 feet), and low (1.6 feet) by the end of the century. Key caveats include the assumption of constant population and demographics, the exclusion of local coastal defenses like sea walls, and the lack of consideration for future adaptation measures.

The guidance note outlines the processes for evaluating the climate impact of water infrastructure bonds. It details a Mitigation Assessment to quantify greenhouse gas (GHG) emissions reductions against baselines and an Adaptation & Resilience Assessment based on a binary scorecard. The latter evaluates an issuer's Vulnerability Assessment and Adaptation Plan across four key areas: water allocation, governance, diagnostic technical assessments (including hydrologic modeling), and the robustness of adaptation strategies. The document emphasizes the use of science-based methodologies, such as the WRI/WBCSD GHG Protocol and IPCC climate projections, and provides extensive examples from the San Francisco Public Utilities Commission to illustrate compliance.

The ALivE tool guides users through a three-phase process: collecting data on livelihoods and ecosystems, analyzing risks and prioritizing EbA options, and integrating these options into policy and planning. It emphasizes a participatory approach, gender sensitivity, and adaptive management to ensure sustainable climate resilience.

The ALivE tool is a decision-support system that guides users through a three-phase process to build climate resilience. Phase 1 involves gathering data via secondary research and participatory methods. Phase 2 uses the tool to analyse risks, identify and prioritise EbA options based on effectiveness and feasibility, and design project activities. Phase 3 focuses on integrating these options into broader policies and planning processes to ensure sustainability and scale.

The guide introduces the ALivE tool, which uses a step-by-step process to analyze the relationship between ecosystems, livelihoods, and climate change. It defines Ecosystem-based Adaptation (EbA) as the use of biodiversity and ecosystem services as part of an adaptation strategy to help people adapt to the adverse effects of climate change. The tool guides users through five modules: understanding the context, analyzing vulnerabilities, identifying EbA options, planning implementation, and establishing monitoring and evaluation (M&E) frameworks. It emphasizes participatory approaches, gender sensitivity, and the integration of EbA into national policies and National Adaptation Plans (NAPs).

RMI's Sunshine for Mines program proposes a systematic approach to repurposing legacy mine sites, which are often liabilities due to contamination and maintenance costs, into productive energy assets. The methodology involves a multi-stage screening process covering environmental and regulatory constraints, technical feasibility (resource screening and reserve quantification), and financial viability via Net Present Value (NPV) calculations. The brief highlights that while mining companies often face high hurdle rates, the economic case is strengthened when compared to the 'business-as-usual' cost of maintaining closed sites. A practical application of this model with BHP in North America identified a subset of sites with a collective potential exceeding 0.5 GW, primarily for solar PV.

The document introduces a practice guide developed by the Canadian Audit and Accountability Foundation, in collaboration with IISD and Women Deliver, to assist auditors in conducting performance audits related to gender equality and the United Nations Sustainable Development Goals.

The document describes the use of Palmes-type NO2 diffusion tubes to monitor air quality across several Brussels locations from 19 February to 20 March 2017. It details the placement of tubes according to Directive 2008/50/EC, the laboratory analysis by Gradko International Limited, and a validation process at the Avenue de la Couronne station which revealed a 24% under-estimation of concentrations by the diffusion tubes. ClientEarth notes it adopted a conservative approach by using the lowest recorded concentrations for locations with multiple samples and publishing raw data without applying the bias correction factor.

This report details the methodology for selecting 'champion' Climate-Smart Agriculture (CSA) options in Nepal, focusing on a screening process that combines expert judgment with farmer feedback to identify 17 champion CSAs or packages across different agro-ecological regions.

The document details the methodology for the Global Landscape of Climate Finance 2017, defining climate finance as capital flows for low-carbon and climate-resilient development. It specifies the inclusion of mitigation, adaptation, and dual-benefit finance while excluding fossil fuel-based lower-carbon generation and private R&D. The accounting scope focuses on annual financial commitments, covering grants, loans, equity, and balance sheet financing, while excluding risk management instruments and secondary market transactions to avoid double counting. It further defines the classification of public and private finance, the data sources used (such as BNEF and OECD), and the sectoral breakdowns for mitigation and adaptation activities.

The document details a spreadsheet model designed to quantify the effects of hypothetical green banks in Maine, New Hampshire, and Vermont from 2017 to 2031. It outlines the financial assumptions, including initial capitalization based on New York's per-capita rates, a 5% borrower interest rate, and a 5:1 private-sector leverage ratio. The methodology explains how funds are allocated across energy efficiency, solar photovoltaics, and community wind, and how these investments are translated into installed capacity, electricity savings, and avoided carbon emissions using data from NREL, ACEEE, and the EPA.