The Green BRI Platform brings together asset-level data tied to ownership across key sectors and markets and overlays this with current and forward-looking measures of environmental risk and impact.
Exposure can be measured and analysed at different scales moving from the asset-level, to the company-level, and to the portfolio-level as required. Existing and planned assets are also assessed and exposure measured over the short-, medium-, and long-term.
The platform allows for the measurement of the environmental impacts associated with investments, locally and globally, such as whether investments are compatible with carbon budgets or are contributing to the unsustainable use of finite natural resources.
The project is pioneering a ‘4th generation’ data and analysis capability across six sectors in BRI jurisdictions: power generation, cement, iron and steel, automobiles, aviation, and shipping. Depending on technical feasibility it has the ambition to include other sectors, including power grids, road, rail, food and beverage manufacturing and processing, paper, refining, mining, upstream oil and gas, pipelines, and LNG infrastructure.
Analysis of stranded asset risks has developed as follows: The 1st generation looked at carbon budgets and whether the reserves were compatible with carbon budgets. The 2nd generation looked at assets owned by companies and then depreciated these based on carbon budgets. The 3rd generation has built on this, but examines assets in much more detail using novel datasets and assesses them across a much wider range of environmental risks and impacts.
The most advanced ‘3rd generation’ asset-level approaches being applied today utilise asset-level data tied to ownership and combine this with overlays of current and forward-looking measures of risk and impact linked to scenarios. This enables sophisticated, granular, and customisable analyses of the exposure of a wide range of investments to different factors – from physical climate change impacts (e.g. flooding, heat stress, and water stress) through to policy (e.g. carbon pricing, air pollution regulation, water pricing) and technological change (e.g. renewables, gas, electric vehicles).
Exposure can be measured and analysed at different scales moving from the asset-level, to the company- level, and to the portfolio-level (e.g. country or investor) as required. Existing and planned assets can be assessed and exposure measured over the short-, medium-, and long-term. Crucially, this approach also allows for the measurement of the environmental impacts associated assets, such as whether investments are compatible with carbon budgets or are contributing to unsustainable resource use.
4th generation data and analysis dramatically increases the speed, breadth, and ‘bandwidth’ of 3rd generation processes and data. It introduces new satellite and remote sensing data, big data, and the application of machine learning and AI. This significantly expands the data capture and data processing capabilities available.
4th generation approaches can automate a large part of this and significantly speed up the research process. It can also more readily generate tailored outputs to different types of users, including spatial analysis.
Comparison of carbon budgets and listed reserves and resources of upstream fossil fuel companies
Depreciation and impairment of fossil fuel company assets based on carbon budgets
Current and forward looking measures of environment risk and opportunity across a wide range of industries and asset types
The incorporation of remote sensing, big data, and advanced analytics into analysis and streamlined ‘on-demand’ delivery of data and analysis