In the last years, humans dramatically altered earth systems. Forests are cut faster than they can regrow, green house gas emissions cause severe global warming and new chemical substances pollute aquatic and terrestrial ecosystems. Consumption and energy demand drive most of these impacts.
Because of the global economy with complex supply chains, production and consumption often occur in different countries and so do the involved impacts.
Environmental extended multi-regional input-output tables (EEMRIOs) facilitate the tracing of goods and it's embodied environmental impacts from the producer to the final consumer. Therewith it is possible to analyse global pollution and resource use through the whole supply chain and consequently calculate footprint (eg carbon, water, ecological) accounts.
Compiling global MRIO is a complex task, and to date six such tables / databases have been compiled. Most of these databases are freely available. However, their structures differ from model to model, and handling/analysing MRIOs needs a certain degree of training.
The pymrio module aims to ease the handling of global MRIOs. With just a couple of commands it is possible to calculate footprints of products, regions or capita. It allows to aggregate countries to regions (eg. EU) and to modify the sector classifications.
In its core, pymrio consists of a set of pandas dataframes coupled with EEMRIO specific API functions. Currently, pymrio includes methods for
The next development steps for pymrio are to implement methods for determining the source of impacts, in depth analysis of the MRIO system and parsing further MRIO systems.
