Read directly from the UNFCCC Data Inventory

The UNFCCC hosts a public Data Inventory of national greenhouse gas emissions. The inventory has a flexible API to retrieve the data, and the Python package unfccc-di-api provides an elegant wrapper to query the API.

The pyam package uses this API and package to retrieve the data and cast it to an IamDataFrame using variable names similar to the structure used in the IPCC process and IAM comparison projects.

Read the UNFCCC Data Inventory FAQ to learn more about the sources of the data and the conditions for using it in own work,

most importantly the request to cite the UNFCCC and other sources.

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Developers note: To reduce the load on Read The Docs, this notebook is not executed by nbsphinx and has to be saved with output.

import pyam

Query the UNFCCC Data Inventory

df = pyam.read_unfccc(party_code='DEU', gases=['CH4'], tier=1)
df

<class 'pyam.core.IamDataFrame'>
Index dimensions:
 * model    : UNFCCC (1)
 * scenario : Data Inventory (1)
Timeseries data coordinates:
   region   : DEU (1)
   variable : Emissions|CH4|Agriculture, Emissions|CH4|Energy, ... Emissions|CH4|Waste (5)
   unit     : kt CH4 (1)
   year     : 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, ... 2018 (29)
Meta indicators:
   exclude (bool) False (1)

Convert emissions to CO2-equivalent using a specific IPCC metric

pyam provides an endogenous feature to convert emissions species using a specific GWP metric. Take a look at this tutorial to learn more!

df.convert_unit('kt CH4', 'Mt CO2e', context='AR4GWP100', inplace=True)

Plot the data

The package includes a number of plotting features with sensible default settings for scenario timeseries analysis.

Visit the plotting gallery to see the range of visualization options!

df.plot(legend={'loc': 'outside right'})

df.plot.stack()

<AxesSubplot:title={'center':'model: UNFCCC scenario: Data Inventory region: DEU'}, xlabel='Year', ylabel='Mt CO2e'>