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Many more individuals are aware of their personal actions such as what, when and how they consume and their impact on the planet. However calculating the environmental impact of day to day actions are pretty difficult and time consuming. Most of the current solutions require users to enter their activities manually, which discourages them over time.

Cleanse.earth uses customers' purchase data to analyze their carbon footprint and give them smart recommendations if needed. Customers are not required to enter their data manually, since the application will be fetching users' data from their bank account using state of the art security measurements.

Customers however, can divide a transaction into different categories manually to get more accurate carbon footprint calculation.

We were not able to implement a solution, because it takes a little bit more time to access the import/export databases.

However here we would like to include an open source project which shows that our concept is possible. Jupyter Notebook can be found on https://github.com/tmrowco/northapp-contrib/blob/master/co2eq/purchase/exiobase/io/carbon_footprint_scopes.ipynb