Articles | Volume 9, issue 8
https://doi.org/10.5194/bg-9-3437-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-9-3437-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
30 Aug 2012
Research article |
| 30 Aug 2012
Global estimates of carbon stock changes in living forest biomass: EDGARv4.3 – time series from 1990 to 2010
A. M. R. Petrescu
DG Joint Research Centre – European Commission, Institute for Environment and Sustainability (IES) Air and Climate Unit, Via Enrico Fermi 2749, 21027 ISPRA (VA), Italy
R. Abad-Viñas
DG Joint Research Centre – European Commission, Institute for Environment and Sustainability (IES) Forest Unit, Via Enrico Fermi 2749, 21027 ISPRA (VA), Italy
G. Janssens-Maenhout
DG Joint Research Centre – European Commission, Institute for Environment and Sustainability (IES) Air and Climate Unit, Via Enrico Fermi 2749, 21027 ISPRA (VA), Italy
V. N. B. Blujdea
DG Joint Research Centre – European Commission, Institute for Environment and Sustainability (IES) Forest Unit, Via Enrico Fermi 2749, 21027 ISPRA (VA), Italy
Forest Research and Management Institute, B-dul Eroilor 128, 077190 Voluntari (Ilfov), Romania
G. Grassi
DG Joint Research Centre – European Commission, Institute for Environment and Sustainability (IES) Forest Unit, Via Enrico Fermi 2749, 21027 ISPRA (VA), Italy
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Cited
15 citations as recorded by crossref.
- Carbon implications of converting cropland to bioenergy crops or forest for climate mitigation: a global assessment F. Albanito et al. 10.1111/gcbb.12242
- CO2 Transport, Variability, and Budget over the Southern California Air Basin Using the High-Resolution WRF-VPRM Model during the CalNex 2010 Campaign C. Park et al. 10.1175/JAMC-D-17-0358.1
- A globally applicable indicator of the capacity of terrestrial ecosystems to retain biological diversity under climate change: The bioclimatic ecosystem resilience index S. Ferrier et al. 10.1016/j.ecolind.2020.106554
- A Knowledge-Aided Robust Ensemble Kalman Filter Algorithm for Non-Linear and Non-Gaussian Large Systems S. Lopez-Restrepo et al. 10.3389/fams.2022.830116
- Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years X. Zhou et al. 10.1186/s40663-019-0208-9
- Improving Air Pollution Modelling in Complex Terrain with a Coupled WRF–LOTOS–EUROS Approach: A Case Study in Aburrá Valley, Colombia J. Hinestroza-Ramirez et al. 10.3390/atmos14040738
- Improving plot-level above ground biomass estimation in tropical Indian forests R. Fararoda et al. 10.1016/j.ecoinf.2024.102621
- EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012 G. Janssens-Maenhout et al. 10.5194/essd-11-959-2019
- Estimating aboveground net biomass change for tropical and subtropical forests: Refinement of IPCC default rates using forest plot data D. Requena Suarez et al. 10.1111/gcb.14767
- Forecasting PM10 and PM2.5 in the Aburrá Valley (Medellín, Colombia) via EnKF based data assimilation S. Lopez-Restrepo et al. 10.1016/j.atmosenv.2020.117507
- Global Forest Resources Assessment 2015: What, why and how? K. MacDicken 10.1016/j.foreco.2015.02.006
- Forest biomass carbon dynamics (1980–2009) in western Himalaya in the context of REDD+ policy A. Wani et al. 10.1007/s12665-017-6903-3
- Models for reporting forest litter and soil C pools in national greenhouse gas inventories: methodological considerations and requirements M. Didion et al. 10.1080/17583004.2016.1166457
- Improving forest above ground biomass estimates over Indian forests using multi source data sets with machine learning algorithm R. Fararoda et al. 10.1016/j.ecoinf.2021.101392
- The EU greenhouse gas inventory for the LULUCF sector: I. Overview and comparative analysis of methods used by EU member states V. Blujdea et al. 10.1080/17583004.2016.1151504
14 citations as recorded by crossref.
- Carbon implications of converting cropland to bioenergy crops or forest for climate mitigation: a global assessment F. Albanito et al. 10.1111/gcbb.12242
- CO2 Transport, Variability, and Budget over the Southern California Air Basin Using the High-Resolution WRF-VPRM Model during the CalNex 2010 Campaign C. Park et al. 10.1175/JAMC-D-17-0358.1
- A globally applicable indicator of the capacity of terrestrial ecosystems to retain biological diversity under climate change: The bioclimatic ecosystem resilience index S. Ferrier et al. 10.1016/j.ecolind.2020.106554
- A Knowledge-Aided Robust Ensemble Kalman Filter Algorithm for Non-Linear and Non-Gaussian Large Systems S. Lopez-Restrepo et al. 10.3389/fams.2022.830116
- Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years X. Zhou et al. 10.1186/s40663-019-0208-9
- Improving Air Pollution Modelling in Complex Terrain with a Coupled WRF–LOTOS–EUROS Approach: A Case Study in Aburrá Valley, Colombia J. Hinestroza-Ramirez et al. 10.3390/atmos14040738
- Improving plot-level above ground biomass estimation in tropical Indian forests R. Fararoda et al. 10.1016/j.ecoinf.2024.102621
- EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012 G. Janssens-Maenhout et al. 10.5194/essd-11-959-2019
- Estimating aboveground net biomass change for tropical and subtropical forests: Refinement of IPCC default rates using forest plot data D. Requena Suarez et al. 10.1111/gcb.14767
- Forecasting PM10 and PM2.5 in the Aburrá Valley (Medellín, Colombia) via EnKF based data assimilation S. Lopez-Restrepo et al. 10.1016/j.atmosenv.2020.117507
- Global Forest Resources Assessment 2015: What, why and how? K. MacDicken 10.1016/j.foreco.2015.02.006
- Forest biomass carbon dynamics (1980–2009) in western Himalaya in the context of REDD+ policy A. Wani et al. 10.1007/s12665-017-6903-3
- Models for reporting forest litter and soil C pools in national greenhouse gas inventories: methodological considerations and requirements M. Didion et al. 10.1080/17583004.2016.1166457
- Improving forest above ground biomass estimates over Indian forests using multi source data sets with machine learning algorithm R. Fararoda et al. 10.1016/j.ecoinf.2021.101392
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