TCFD defines transition risks as arising from the shift toward a low-carbon economy, including changes in regulation, carbon pricing, technological innovation, and evolving market dynamics. While carbon pricing is a central policy tool designed to incentivise emissions reduction, transition risk extends beyond direct carbon costs. It also encompasses structural changes in demand, competitiveness, and sectoral growth patterns driven by decarbonisation pathways.

Accordingly, our transition risk assessment does not rely solely on carbon intensities and carbon tax assumptions. In addition to modelling carbon cost exposure, we incorporate scenario-based sector–country revenue projections as a proxy for market demand shifts under different climate pathways. This enables us to capture how policy developments, technology adoption, and changing investor and consumer preferences may affect revenues across sectors and geographies.

By combining carbon cost impacts with forward-looking revenue dynamics, we provide a comprehensive view of transition risk, translating both cost-side pressures and demand-side shifts into financial impacts on cash flows and asset valuation.

Multiple years of research support our carbon metrics estimates. This includes the use of The Infrastructure Company and Classification Standard (TICCS) to classify infrastructure assets, as well as the TICCS+ Taxonomy and EDHEC Materiality Profiles to identify assets’ main activities and operations, their primary technologies, and their main sources of emissions. Our estimates further rely on public research articles that specify sector activities and reports from reliable institutions (e.g., EIA, IEA, NREL, World Bank), among others. For more details, please refer to our S1+2 and S3 methodology documents.

Data availability for some infrastructure sectors remains a challenge. Accordingly, some of our emission estimations rely on revenue- or activity-based models rather than statistical calibration. However, by combining a variety of data sources with reliable approaches and aligning them with widely accepted standards, such as the Greenhouse Gas Protocol, we can gain valuable and reliable insights into patterns of carbon intensity across TICCS superclasses. Moreover, our methods and models are validated against emission estimates from various sources, including international organisations (e.g. World Bank, WRI, EIA) and reported data from companies’ sustainability reports.

We provide carbon intensities by revenue for Scope 1+2 and Scope 3 emissions at the asset/company level.  For all approaches, we aim to include as much reported data on S1+2 emissions as possible to improve the robustness of the results. For Scope 3 carbon emission intensities, our methodology estimates these using a top-down approach. Our approach focuses on systematic features common to assets within the same sector rather than idiosyncratic characteristics, which are difficult to capture for multi-tiered supply chains. We focus specifically on the operational upstream and downstream activities of infrastructure assets, excluding emissions from the construction and disposal phases.

We calculate Data Quality Scores (DQS) for the data used to quantify Scope 1, Scope 2, and Scope 3 emissions.  The DQS offers decreasing quality scores ranging from 1 to 5, inspired by PCAF.

Yes, we do consider the effects of future climate scenarios. All our underlying metrics are available across seven scenarios that describe possible pathways for a large number of macro-financial quantities, spanning two time horizons: until 2035 and 2050. For the Climate Exposure Rating, we calculate all metrics under the most likely scenario, while for the Climate Risk Rating, we consider the weighted averages across all scenarios, based on their probabilities.

All metrics are aligned with well-accepted international standards, like the Greenhouse Gas Protocol and the Partnership for Carbon Accounting Financials (PCAF). If available, our methodology follows additional recommendations from sector-specific institutions. We further provide a Data Quality Score (DQS) that highlights the reliability and precision of the underlying data. The DQS are aligned with PCAF, offering a clear benchmark to evaluate data completeness, consistency, and relevance.

The carbon metrics are updated on an annual basis using multiple sources of data, such as:

• Reported emissions from financial and sustainability reports
• Public information, like public data from international organisations (e.g. the World Bank, EIA, WRI), websites of companies, and other reliable sources
• Commercial datasets that provide asset characteristics, such as geolocation, capacities, output production, or volumes of operations

For more details, please refer to our S1+2 and S3 methodology documents.