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Reconciling global-model estimates and country reporting of anthropogenic forest CO2 sinks

Research output: Contribution to journalArticle

  • Giacomo Grassi
  • Jo House
  • Werner A. Kurz
  • Alessandro Cescatti
  • Richard A. Houghton
  • Glen P. Peters
  • Maria J. Sanz
  • Raul Abad Viñas
  • Ramdane Alkama
  • Almut Arneth
  • Alberte Bondeau
  • Frank Dentener
  • Marianela Fader
  • Sandro Federici
  • Pierre Friedlingstein
  • Atul K. Jain
  • Etsushi Kato
  • Charles D. Koven
  • Donna Lee
  • Julia E. M. S. Nabel
  • Alexander A. Nassikas
  • Lucia Perugini
  • Simone Rossi
  • Stephen Sitch
  • Nicolas Viovy
  • Andy Wiltshire
  • Sönke Zaehle
Original languageEnglish
Pages (from-to)914-920
Number of pages10
JournalNature Climate Change
Early online date24 Sep 2018
DateAccepted/In press - 28 Aug 2018
DateE-pub ahead of print - 24 Sep 2018
DatePublished (current) - 24 Sep 2018


Achieving the long-term temperature goal of the Paris Agreement requires forest-based mitigation. Collective progress towards this goal will be assessed by the Paris Agreement’s Global stocktake. At present, there is a discrepancy of about 4 GtCO2 yr−1 in global anthropogenic net land-use emissions between global models (reflected in IPCC assessment reports) and aggregated national GHG inventories (under the UNFCCC). We show that a substantial part of this discrepancy (about 3.2 GtCO2 yr−1) can be explained by conceptual differences in anthropogenic forest sink estimation, related to the representation of environmental change impacts and the areas considered as managed. For a more credible tracking of collective progress under the Global stocktake, these conceptual differences between models and inventories need to be reconciled. We implement a new method of disaggregation of global land model results that allows greater comparability with GHG inventories. This provides a deeper understanding of model–inventory differences, allowing more transparent analysis of forest-based mitigation and facilitating a more accurate Global stocktake.


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