Skip to main content
ICOS Talks inverse modelling

ICOS Talks: Atmospheric measurements and inverse modelling to support national greenhouse gas emissions reporting

08 Jul 2026

Time: Wednesday 8th July 2026, 12:00-13:00 CEST.

Agenda:

  • Introduction by Sindu Raj Parampil (Science Integration Officer, ICOS ERIC)
  • Anita Ganesan (Professor of Atmospheric Chemistry, University of Bristol): Atmospheric measurements and inverse modelling to support national greenhouse gas emissions reporting
  • Discussion and wrap-up

About the speaker

Anita Ganesan is an atmospheric scientist and Professor of Atmospheric Chemistry at the University of Bristol, UK. Her research focuses on greenhouse gases and ozone-depleting substances. Anita specialises in combining atmospheric measurements with modelling to improve understanding of regional and global emissions. She collaborates extensively with international monitoring networks to interpret long-term atmospheric observations. Anita’s research contributes to global assessments and to evidence-based environmental policy.

Abstract

Inverse modelling is a technique used to estimate emissions of greenhouse gases from measured concentrations in the atmosphere. Emissions derived from inversions are increasingly being used to complement national inventories, the framework by which countries document and report their emissions to the UNFCCC. Using the observing networks in Europe (ICOS, AGAGE, national networks) the Horizon EU PARIS project has used inverse modelling to estimate European CH₄, N₂O and F-gas emissions, focusing on delivering information to the national inventory compilers of eight countries. This presentation will describe the principles behind this method, the key findings in Europe and the ongoing challenges in using atmosphere-derived emissions estimates to support the UNFCCC process.   

 

Registration is required for this webinar. Click here to register.


EU flag

New Users for a Better ICOS (NUBICOS) received funding from the European Union’s Horizon Europe programme under grant agreement no. 101130676