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Increased Amazon carbon emissions mainly from decline in law enforcement

Nature volume 621, pages 318–323 (2023)Cite this article

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Abstract

The Amazon forest carbon sink is declining, mainly as a result of land-use and climate change1,2,3,4. Here we investigate how changes in law enforcement of environmental protection policies may have affected the Amazonian carbon balance between 2010 and 2018 compared with 2019 and 2020, based on atmospheric CO2 vertical profiles5,6, deforestation7 and fire data8, as well as infraction notices related to illegal deforestation9. We estimate that Amazonia carbon emissions increased from a mean of 0.24 ± 0.08 PgC year−1 in 2010–2018 to 0.44 ± 0.10 PgC year−1 in 2019 and 0.52 ± 0.10 PgC year−1 in 2020 (± uncertainty). The observed increases in deforestation were 82% and 77% (94% accuracy) and burned area were 14% and 42% in 2019 and 2020 compared with the 2010–2018 mean, respectively. We find that the numbers of notifications of infractions against flora decreased by 30% and 54% and fines paid by 74% and 89% in 2019 and 2020, respectively. Carbon losses during 2019–2020 were comparable with those of the record warm El Niño (2015–2016) without an extreme drought event. Statistical tests show that the observed differences between the 2010–2018 mean and 2019–2020 are unlikely to have arisen by chance. The changes in the carbon budget of Amazonia during 2019–2020 were mainly because of western Amazonia becoming a carbon source. Our results indicate that a decline in law enforcement led to increases in deforestation, biomass burning and forest degradation, which increased carbon emissions and enhanced drying and warming of the Amazon forests.

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Fig. 1: Amazonia annual mean vertical profiles.
Fig. 2: Amazonia deforestation anomaly map for 2019 and 2020.
Fig. 3: Environmental law enforcement and accountability for crimes against the Amazon forest.
Fig. 4: Amazonia carbon flux 2010–2020.

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Data availability

The CO2 vertical profile data that support the findings of this study are available from PANGAEA Data Archiving at https://doi.org/10.1594/PANGAEA.926834 for data from 2010 to 2018. For data from 2019 and 2020, they are available at https://doi.pangaea.de/10.1594/PANGAEA.949643. Together with the CO2 and CO data are also available time trajectories, region of influence shape files, background, all variables used in the study, and Excel files.

Code availability

The uncertainty code is available at https://doi.pangaea.de/10.1594/PANGAEA.949643.

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Acknowledgements

This work was funded by many projects from the long-term measurements: State of Sao Paulo Science Foundation – FAPESP (16/02018-2, 11/51841-0, 08/58120-3, 21/09020-0, 18/14006-4, 18/14423-4, 18/18493-7, 19/21789-8, 11/17914-0), UK Natural Environmental Research Council (NERC) AMAZONICA project (NE/F005806/1), NASA grants (11-CMS11-0025, NRMJ1000-17-00431), Seventh Framework Programme (7FP) EU (283080), MCTI/CNPq (2013), CNPq (134878/2009-4, 444418/2018-0), ERC/Horizon 2020 (649087), PPGCST/INPE and PROEX/CAPES. We thank the many people at the NOAA/GML who provided advice and technical support for air sampling and measurements in Brazil and the pilots and technical team at aircraft sites who collected the air samples. We thank J. F. Mueller for providing modelled biogenic CO fluxes.

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Authors and Affiliations

  1. General Coordination of Earth Science (CGCT), National Institute for Space Research (INPE), São José dos Campos, Brazil

    Luciana V. Gatti, Camilla L. Cunha, Luciano Marani, Henrique L. G. Cassol, Cassiano Gustavo Messias, Egidio Arai, Luciana S. Soler, Claudio Almeida, Alberto Setzer, Luana S. Basso, Caio S. C. Correia, Graciela Tejada, Raiane A. L. Neves, Alber H. Sanches, Luiz E. O. C. Aragão, Celso Von Randow, Stephane P. Crispim, Francine M. Silva & Guilherme B. M. Machado

  2. Nuclear and Energy Research Institute (IPEN), São Paulo, Brazil

    Luciana V. Gatti, Lucas Gatti Domingues & Caio S. C. Correia

  3. Colorado State University, Fort Collins, CO, USA

    A. Scott Denning

  4. National Isotope Centre, GNS Science, Lower Hutt, New Zealand

    Lucas Gatti Domingues

  5. Global Monitoring Laboratory, National Oceanic and Atmospheric Administration (NOAA), Boulder, CO, USA

    John B. Miller

  6. School of Geography, University of Leeds, Leeds, UK

    Manuel Gloor

  7. Remote Sensing Center, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Raoni Rajao, Felipe Nunes, Britaldo S. S. Filho & Jair Schmitt

  8. Instituto de Estudos Avançados (IEA), University of São Paulo (USP), São Paulo, Brazil

    Carlos Nobre

  9. Rio de Janeiro State University (UERJ), Rio de Janeiro, Brazil

    Sergio M. Corrêa

  10. Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN), São José dos Campos, Brazil

    Liana Anderson

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  1. Luciana V. Gatti
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Contributions

L.V.G., M.G. and J.B.M. conceived the basin-wide measurement programme and approach. L.V.G. wrote the paper. All co-authors commented on and reviewed the manuscript. L.V.G., C.L.C. and L.M. performed the analysis of results. L.G.D., A.S., L.M. and L.V.G. contributed the region of influence study. H.L.G.C., E.A., C.L.C., L.M. and L.V.G. contributed the climate data weighted studies. C.G.M., L.S.S., C.A. and A.S. contributed the deforestation and fire spots analyses. L.G.D., C.S.C.C., S.P.C., R.A.L.N., F.M.S. and G.B.M.M. contributed the greenhouse gas concentration analysis. R.R., F.N., B.S.S.F. and J.S. contributed the law enforcement analysis. J.B.M. and L.V.G. contributed the estimate of the biogenic CO. S.M.C. produced the analysis of human economic activities in the Amazon region. C.L.C. produced the missForest and statistical analysis.

Corresponding author

Correspondence to Luciana V. Gatti.

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Competing interests

The authors declare no competing interests.

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Peer review information

Nature thanks Christiane Derani, Steve Wofsy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Regions of influence.

Annual mean regions of influence based on back trajectories density, calculated by the HYSPLIT trajectory model for each flask, on each vertical profile along all studied years (2010–2018) for the sites SAN (2.9° S, 55.0° W), RBA (9.4° S, 67.6° W); 2010–2012 for TAB (6.0° S, 70.1° W); and from 2013 for TEF (3.4° S, 65.6° W) (see Methods).

Extended Data Fig. 2 Annual mean ΔVPs per site.

Annual mean ΔVPs for each site TAB_TEF, SAN, RBA, and ALF for the time series (2010–2020), constructed from the annual mean vertical profile, in which the background was subtracted from each height, and each flask (see Methods). The thick black lines represent the 2010–2018 Amazonia sites mean vertical profiles, the thick red lines the 2019 mean and the thick blue lines the 2020 mean.

Extended Data Fig. 3 Amazonia’s deforestation, law enforcement, and fire spots time series.

a, Deforestation limited to the Brazilian Amazonia classified as the Legal Amazon (km2) by PRODES/INPE7 from 2000 to 2020. b, Annual infraction notices without geographic coordinates (grey bars) and with geographic coordinates (orange bars). The blue line represents the embargoes and the green line represents seizures, applied by IBAMA for crimes against flora in the Legal Amazon. c, Fire spots limited to the Brazilian Amazonia classified as Biome Amazonia by BDQueimadas/INPE8 from 2000 to 2020.

Extended Data Fig. 4 Amazonia fire spot anomaly map and distribution.

Fire spots in Pan Amazonia are given in grid cells 0.25° × 0.25° and were retrieved from INPE’s ‘Queimadas’ wildfire monitoring programme8. a, 2019 anomaly compared with the mean fire spot per grid between 2010 and 2018. b, 2020 anomaly compared with the mean fire spot per grid between 2010 and 2018. c, Fire spots detected at Amazonas state from 2010 to 2020. The black line denotes 2010–2018 mean, the grey band denotes the standard deviation of the monthly mean, the red line the 2019 monthly mean and the blue line the 2020 monthly mean. d, Fire spots detected at Roraima state from 2010 to 2020.

Extended Data Fig. 5 Amazonia crops area, cattle and wood exportation.

Increase in the replacement of forest by soybean, corn, beef and wood commerce as a consequence of deforestation. a, Evolution of harvested area of soybean (black line), corn (dashed line)27 and wood exportation (red line)26. b, Cattle production evolution inside (black line) and outside Amazonia, that is, in other Brazilian states (blue line)28. a and b were built using official data from the Brazilian government.

Extended Data Fig. 6 Annual mean carbon fluxes FCTotal, FCNBE and FCFire.

a, Separation of three different areas inside the Amazon mask (7,256,362 km2, purple line) using mean annual influence regions of all years (2010–2018). Region 1: combined ALF and SAN regions of influence; region 2: combined RBA and TAB (2010–2012) and TEF (2013–2018) to compose region of influence 2 and excluding region 1 for the quantification; region 3: the remaining area outside regions 1 and 2 and inside the purple line. b, The annual mean total carbon fluxes (FCTotal), net biome exchange (FCNBE) and fire carbon fluxes (FCFire) were calculated according to the regional distribution shown on the map in a.

Extended Data Fig. 7 El Niño/La Niña episodes (ONI) and seasonal precipitation and temperature.

a, Warm (red) and cold (blue) periods based on a threshold of +/−0.5 °C for the Oceanic Niño Index (ONI) (three-month running mean of ERSST.v5 sea-surface temperature anomalies in the Niño 3.4 region (5° N–5° S, 120°–170° W)), based on 30-year base periods revised every 5 years (ref. 42). b, Seasonal monthly Amazon mean precipitation 2010–2018 (solid light blue line) and temperature (solid brown line). The grey bar is the standard deviation for the monthly means 2010–2018, the dashed line for precipitation and temperature 2019 and the dotted line for precipitation and temperature 2020.

Extended Data Fig. 8 Amazonia carbon fire and NBE flux 2010–2020.

a, Monthly means for Amazonia fire carbon flux (FCFire). The black line denotes 2010–2018 mean, in which the grey bands denote the standard deviation of the monthly mean, the red line 2019 and the blue line 2020. b, Annual mean Amazonia net biome exchange (NBE: FCTotal − FCFire). c, Annual mean Amazonia Fire carbon flux time series and d, As in c, Annual mean net biome exchange (see Methods).

Extended Data Fig. 9 Amazonia results overview.

Summary of total carbon flux (white box), fire carbon flux (red box), net biome exchange (green box) and deforestation per site (orange box). The boxes are all related to the 2010–2018 mean and 2019 (pink arrows) and 2020 (blue arrows) for all fluxes (gC m−2 day−1) and deforestation (km2).

Extended Data Table 1 Summary results for all sites
Full size table

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Gatti, L.V., Cunha, C.L., Marani, L. et al. Increased Amazon carbon emissions mainly from decline in law enforcement. Nature 621, 318–323 (2023). https://doi.org/10.1038/s41586-023-06390-0

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