Updated: Jun 22
There is a strong drive from the finance industry, and regulation, for more rigorous, transparent and reliable carbon accounting. The members of the Partnership for Carbon Accounting Financials (PCAF) manage assets and investments in excess of $US92 Trillion and they are setting their own target for reporting Scope 3 GHG emissions by 2026.
The longevity of investments, loans and other financial products means that the finance sector seeks quality information for decisions now, in order to mitigate climate-related risk over the lifetime of their investments. Climate risk as investment risk in the finance sector manifests in:
Physical risk — exposure to extreme weather, ecological impacts, gradual and extreme
Transition Risk — policy or technology change, and social responses
Liability Risk — failure to mitigate, adapt or disclose
The latter two of these relate more to the response to climate change: the climate transition and global decarbonization trend, where investments may be exposed to changing expectations of shareholders, markets and government.
There’s a growing carbon information market and this can connect the governance and reporting requirements of finance, with pragmatic needs of business. However, data for research and scientists is different, and used differently, compared with data used by the market. How to translate academic techniques to applications?
FootprintLab has been founded by two long-time members of the International Society for Industrial Ecology (ISIE) with the intent to take the data, the rigor and the transparency demanded by industrial ecology research, and make it broadly available for commercial application. FootprintLab is a for-profit social enterprise that returns revenue to the research institutions who maintain the global environmentally extended Multi-Regional Input-Output models (MRIO) that are the main sources of data.
Our initial surveys of the market have found preferences for data reliability, currency and ease of use. At the same time that commercial users ask for greater detail or granularity in data, they also recognize that sufficient accuracy may be enough to make a decision.
Ideally these requirements would be served by a globally complete data set of companies and their products, and their respective carbon intensity relating to purchases or activity using those products. Such an ideal does not yet exist though there may be a possibility of leveraging incoming technology such as digital trade, IOT, fintech, machine learning and artificial intelligence to create reliable, dynamic data sets.
In the meantime, globally, there are a limited number of data resources that connect monetary flows with environmental impact (through MRIO models), for example: EORA, WIOD, EXIOBASE, the GTAP-based OpenEU, and GLORIA. Although broadly consistent at a macro-economic level, they differ in features at the level of commercial interest.
Another part of FootprintLab's purpose is to improve 'carbon literacy' in the carbon data consumer: to deliver credible numbers and also information on data provenance, measures of accuracy, and appropriate use.
We believe standards of (financial) governance should be accompanied with standards of data provenance, validity and application to carbon accounting. Then the burgeoning carbon information market can present useful, credible and transparent information for spending and investment decisions.