Harmonising the land-use flux estimates of global models and national inventories for 2000–2020
Authors: Grassi Giacomo , Schwingshackl Clemens , Gasser Thomas , Houghton Richard A. , Sitch Stephen , Canadell Josep G. , Cescatti Alessandro , Ciais Philippe , Federici Sandro , Friedlingstein Pierre , Kurz Werner A. , Sanz Sanchez Maria J. , Abad Viñas Raúl , Alkama Ramdane , Bultan Selma , Ceccherini Guido , Falk Stefanie , Kato Etsushi , Kennedy Daniel , Knauer Jürgen , Korosuo Anu , Melo Joana , McGrath Matthew J. , Nabel Julia E. M. S. , Poulter Benjamin , Romanovskaya Anna A. , Rossi Simone , Tian Hanqin , Walker Anthony P. , Yuan Wenping , Yue Xu , Pongratz Julia 
Published: March 2023

Abstract. As the focus of climate policy shifts from pledges to implementation, there
is a growing need to track progress on climate change mitigation at the
country level, particularly for the land-use sector. Despite new tools and
models providing unprecedented monitoring opportunities, striking
differences remain in estimations of anthropogenic land-use CO2 fluxes
between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess
compliance with national climate targets under the Paris Agreement and, on the other hand, the
Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global
bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to
inconsistent definitions of anthropogenic CO2 fluxes in managed
forests. Countries assume larger areas of forest to be managed than BMs do, due
to a broader definition of managed land in NGHGIs. Additionally, the
fraction of the land sink caused by indirect effects of human-induced
environmental change (e.g. fertilisation effect on vegetation growth due to
increased atmospheric CO2 concentration) on managed lands is treated as
non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the
CO2 sink caused by environmental change in countries' managed forests
(estimated by 16 dynamic global vegetation models, DGVMs) to the
land-use fluxes from three BMs. This sum is conceptually more comparable to
NGHGIs and is thus expected to be quantitatively more similar. Our analysis
uses updated and more comprehensive data from NGHGIs than previous studies
and provides model results at a greater level of disaggregation in terms of
regions, countries and land categories (i.e. forest land, deforestation,
organic soils, other land uses). Our results confirm a large difference (6.7 GtCO2 yr−1) in global
land-use CO2 fluxes between the ensemble mean of the BMs, which
estimate a source of 4.8 GtCO2 yr−1 for the period 2000–2020,
and NGHGIs, which estimate a sink of −1.9 GtCO2 yr−1 in the same
period. Most of the gap is found on forest land (3.5 GtCO2 yr−1),
with differences also for deforestation (2.4 GtCO2 yr−1), for fluxes
from other land uses (1.0 GtCO2 yr−1) and to a lesser extent for
fluxes from organic soils (0.2 GtCO2 yr−1). By adding the DGVM
ensemble mean sink arising from environmental change in managed forests
(−6.4 GtCO2 yr−1) to BM estimates, the gap between BMs and NGHGIs
becomes substantially smaller both globally (residual gap: 0.3 GtCO2 yr−1) and in most regions and countries. However, some discrepancies
remain and deserve further investigation. For example, the BMs generally
provide higher emissions from deforestation than NGHGIs and, when adjusted
with the sink in managed forests estimated by DGVMs, yield a sink that is
often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations
of anthropogenic land-use fluxes, allowing for detailed comparisons between
global models and national inventories at global, regional and country
levels. This is crucial to increase confidence in land-use emissions
estimates, support investments in land-based mitigation strategies and
assess the countries' collective progress under the Global Stocktake of the
Paris Agreement. Data from this study are openly available online via the Zenodo portal
(Grassi et al., 2023) at https://doi.org/10.5281/zenodo.7650360.