Abstract
Brazil is currently the largest contributor of land use and land cover change (LULCC) carbon dioxide net emissions worldwide, representing 17%–29% of the global total. There is, however, a lack of agreement among different methodologies on the magnitude and trends in LULCC emissions and their geographic distribution. Here we perform an evaluation of LULCC datasets for Brazil, including those used in the annual global carbon budget (GCB), and national Brazilian assessments over the period 2000–2018. Results show that the latest global HYDE 3.3 LULCC dataset, based on new FAO inventory estimates and multi-annual ESA CCI satellite-based land cover maps, can represent the observed spatial variation in LULCC over the last decades, representing an improvement on the HYDE 3.2 data previously used in GCB. However, the magnitude of LULCC assessed with HYDE 3.3 is lower than estimates based on MapBiomas. We use HYDE 3.3 and MapBiomas as input to a global bookkeeping model (bookkeeping of land use emission, BLUE) and a process-based Dynamic Global Vegetation Model (JULES-ES) to determine Brazil's LULCC emissions over the period 2000–2019. Results show mean annual LULCC emissions of 0.1–0.4 PgC yr−1, compared with 0.1–0.24 PgC yr−1 reported by the Greenhouse Gas Emissions Estimation System of land use changes and forest sector (SEEG/LULUCF) and by FAO in its latest assessment of deforestation emissions in Brazil. Both JULES-ES and BLUE now simulate a slowdown in emissions after 2004 (−0.006 and −0.004 PgC yr−2 with HYDE 3.3, −0.014 and −0.016 PgC yr−2 with MapBiomas, respectively), in agreement with the Brazilian INPE-EM, global Houghton and Nassikas book-keeping models, FAO and as reported in the 4th national greenhouse gas inventories. The inclusion of Earth observation data has improved spatial representation of LULCC in HYDE and thus model capability to simulate Brazil's LULCC emissions. This will likely contribute to reduce uncertainty in global LULCC emissions, and thus better constrains GCB assessments.
| Original language | English |
|---|---|
| Article number | 074004 |
| Number of pages | 13 |
| Journal | Environmental Research Letters |
| Volume | 16 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 22 Jun 2021 |
Bibliographical note
Funding Information:Original content from this work may be used under the terms of the . Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Conselho Nacional de Desenvolvimento Cient�fico e Tecnol�gico http://dx.doi.org/10.13039/501100003593 Natural Environment Research Council NE/L002434/1 Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil) Natural Environment Research Council http://dx.doi.org/10.13039/501100000270 NE/N017951/1 H2020 European Institute of Innovation and Technology http://dx.doi.org/10.13039/100010686 821003 Horizon 2020 Framework Programme 776810 ESA Climate Change Initiative 4000123002/18/I-NB yes � 2021 The Author(s). Published by IOP Publishing Ltd Creative Commons Attribution 4.0 license
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© 2021 The Author(s). Published by IOP Publishing Ltd.
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