Published August 24, 2023 | Version v1
Dataset Open

Machine learning methods for gap-filling in greenhouse gas emissions databases

Authors/Creators

  • 1. University of Cambridge

Description

Datasets for use with code related to "Machine learning methods for gap-filling in greenhouse gas emissions databases" manuscript submitted to the Journal of Industrial Ecology. Code for using the datasets can be found at https://github.com/luke-scot/ml-ghg-databases.

Files

ClimateTRACE.csv

Files (18.4 MB)

Name Size Download all
md5:de5ece9d3b7821b106c8bb43110e9098
2.6 MB Preview Download
md5:1d883a3dc8e57ec34b763d9af687b013
11.4 MB Preview Download
md5:d9ab49a98485c7ae7ccc9ba947ef07ca
4.4 MB Preview Download

Additional details

Funding

UK Research and Innovation
UKRI Centre for Doctoral Training in Application of Artificial Intelligence to the study of Environmental Risks (AI4ER) EP/S022961/1

References