Land-use change emissions based on high-resolution activity data substantially lower than previously estimated

Abstract

Land-use and land-cover changes (LULCCs) contributed around one third to the cumulative, anthropogenic CO2 emissions from 1850 to 2019. Despite its great importance, estimates of the net CO2 fluxes from LULCC (ELUC) have high uncertainties, compared to other components of the global carbon cycle. One major source of uncertainty roots in the underlying LULCC forcing data. In this study, we implemented a new high-resolution LULCC dataset (HILDA+) in a bookkeeping model (BLUE) and compared the results to estimates from simulations based on LUH2, which is the LULCC dataset most commonly used in global carbon cycle models. Compared to LUH2-based estimates, results based on HILDA+ show lower total ELUC (global mean difference 1960–2019: 541 TgC yr−1, 65%) and large spatial and temporal differences in component fluxes (e.g. CO2 fluxes from deforestation). In general, the congruence of component fluxes is higher in the mid-latitudes compared to tropical and subtropical regions, which is to some degree explained with the different implementations of shifting cultivation in the underlying LULCC datasets. However, little agreement is reached on the trend of the last decade between ELUC estimates based on the two LULCC reconstructions. Globally and in many regions, ELUC estimates based on HILDA+ have decreasing trends, whereas estimates based on LUH2 indicate an increase. Furthermore, we analyzed the effect of different resolutions on ELUC estimates. By comparing estimates from simulations at 0.01∘ and 0.25∘ resolution, we find that component fluxes of estimates based on the coarser resolution tend to be larger compared to estimates based on the finer resolution, both in terms of sources and sinks (global mean difference 1960–2019: 36 TgC yr−1, 96%). The reason for these differences are successive transitions: these are not adequately represented at coarser resolution, which has the effect that—despite capturing the same extent of transition areas—overall less area remains pristine at the coarser resolution compared to the finer resolution.

Climate Change and Rising CO2 Amplify the Impact of Land Use/Cover Change on Carbon Budget Differentially Across China

“…Although bookkeeping model has been widely used to track the impact of LUC trajectories on the carbon budget, it failed to take the impact of CCRC into consideration. The coarse LUC map used as the input of bookkeeping also constrained its accuracy to calculate carbon flux (Ganzenmüller et al., 2022). Although ecosystem process‐based models integrate CCRC into carbon flux calculations, rare studies have used them to track the impact of LUCC on the carbon budget under the conditions of CCRC (Erb et al., 2017).…”

Carbon and greenhouse gas budgets of Europe: trends, interannual and spatial variability, and their drivers

“…Note that we did not include We use estimates from H&N as prepared for the Global Carbon Budget 2020 , which used land use data from LUH2 (Hurtt et al 2020). For BLUE, we used data from Ganzenmüller et al (2022) which applied that model to two different land use data sets: LUH2…”

Satellite-based global maps are rarely used in forest reference levels submitted to the UNFCCC

“…EO products with spatial resolutions coarser or finer than the corresponding 70 m and 100 m do not accurately depict forest and forest change extent. For example, coarser pixels may include mixed classes from the national definitions and miss small-scale dynamics (Milodowski et al 2017, Kalamandeen et al 2018, Ganzenmuller et al 2022. For finer resolutions, FRLs using the GFC (30 m pixels, or approximately 0.09 ha) resampled the data to the minimum mapping unit matching the national definition of forest so as not to overestimate the area of forest and deforestation.…”