GHG emissions

COGEM - Corporate GHG emission estimations

This project provides estimates of Greenhouse Gas (GHG) emissions for a vast dataset of over 47 000 listed companies. The emission data are categorized into scopes 1, 2, 3 and 123 (sum of all scopes) for each company. Data is available from 2005 to 2023. With over 650 000 samples, it is, to our knowledge, the largest dataset of its type. It is produced by Machine Learning algorithms, of which the full methodology is detailed in the following SSRN link and the code can be found in the public Github repository.

More Details Data guide

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COGEM emissions database
(Access on demand)

This dataset is the main output of the COGEM project. Based on our proprietary methodology, we allow researchers to access this unique database for in-depth research on sustainable finance topics such as transition risks or regulatory implications.

    Data can be accessed for academic projects for a participation to maintenance costs (1 200€ + management fees), and publications derived from its use are required to cite the following: "Research work realized thanks to Pladifes COGEM project in the context of the Pladifes EquipEx (ANR-21-ESRE-0036), hosted at the Institut Louis Bachelier." Non-academic interested in replicating the methodology are encouraged to contact us directly for further information.
Statistical overview API (Access required) Sample of the dataset Require full access




COGEM online calculator
(Access on demand)

The COGEM Calculator is an innovative tool designed to provide users with an application for calculating their carbon footprint across various scopes. This user-friendly application will enable individuals or organizations to upload their data in compliance with a specified format that is precised in the application and receive accurate estimations for emissions within scopes 1, 2, and 3.

There are two versions of the calculator: the restricted and the unrestricted. The restricted calculator employs a limited set of easily accessible metrics to predict GHG emissions, offering a general estimation. On the other hand, the unrestricted calculator utilizes a more extensive range of specific metrics that might only be accessible from certain data providers. Consequently, the unrestricted tool yields more precise estimations due to its ability to incorporate a broader and more detailed dataset.

Both versions aim to facilitate understanding and management of carbon footprints but offer varying levels of detail and precision based on the user's needs and data availability.For access to these tools and further details, please reach out to our team.
Calculator restricted Calculator unrestricted


References


Scientific papers
- T. Barreau, M. Fahmaoui, P. Tankov, Estimating Corporate Greenhouse Gas Emissions, SSRN (2024).
- Q. Nguyen, I. Diaz-Rainey, and D. Kuruppuarachchi, Predicting corporate carbon footprints for climate finance risk analyses: a machine learning approach, Energy Economics, 95 (2021), p. 105129.
- J. Assael, T. Heurtebize, L. Carlier, and F. Soupé, Greenhouse gases emissions: estimating corporate non-reported emissions using interpretable machine learning, Sustainability, 15 (2023), p. 3391.