Articles | Volume 20, issue 6
https://doi.org/10.5194/acp-20-3439-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-3439-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterization of the radiative impact of aerosols on CO2 and energy fluxes in the Amazon deforestation arch using artificial neural networks
Renato Kerches Braghiere
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, 4800
Oak Grove Drive, Pasadena, CA 91109, USA
Joint Institute for Regional Earth System Science and Engineering,
University of California at Los Angeles, Los Angeles, CA 90095, USA
Departamento de Ciências Atmosféricas, Instituto de
Astronomia, Geofísica e Ciências Atmosféricas, Universidade de
São Paulo, São Paulo, Brazil
current address: NASA Jet Propulsion Laboratory, M/S 233-305F,
4800 Oak Grove Drive, Pasadena, CA 91109, USA
Marcia Akemi Yamasoe
Departamento de Ciências Atmosféricas, Instituto de
Astronomia, Geofísica e Ciências Atmosféricas, Universidade de
São Paulo, São Paulo, Brazil
Nilton Manuel Évora do Rosário
Laboratório de Clima e Poluição do Ar (LabClip), Instituto de Ciências Ambientais, Químicas e Farmacêuticas, Universidade Federal de São Paulo, Diadema, Brazil
Humberto Ribeiro da Rocha
Departamento de Ciências Atmosféricas, Instituto de
Astronomia, Geofísica e Ciências Atmosféricas, Universidade de
São Paulo, São Paulo, Brazil
José de Souza Nogueira
Instituto de Física, Universidade Federal de Mato Grosso, Mato
Grosso, Brazil
Alessandro Carioca de Araújo
Embrapa Amazônia Oriental, Travessa Dr. Enéas Pinheiro, s/n,
Marco, Caixa Postal 48, Belém, Pará 66095-100, Brazil
Instituto Nacional de Pesquisas da Amazônia (INPA), Large Scale Biosphere-Atmosphere Experiment in
Amazonia (LBA), Avenida André Araújo, 2936, Manaus, Amazonas, 69060-001, Brazil
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Cited
13 citations as recorded by crossref.
- Legacy Effects Following Fire on Surface Energy, Water and Carbon Fluxes in Mature Amazonian Forests G. de Oliveira et al. 10.1029/2020JG005833
- Drivers of atmospheric CO2 concentration in southeast Brazil: Insights from land use change, vegetation, and climate factors L. da Costa et al. 10.1016/j.rsase.2025.101614
- Microclima no Cenário de Floresta, Pastagem e Cidade no Sudoeste da Amazônia B. Antonucci et al. 10.1590/0102-778640230038
- Aerosol radiative and climatic effects on ecosystem productivity and evapotranspiration H. Zhou et al. 10.1016/j.coesh.2020.10.006
- Vegetation clumping modulates global photosynthesis through adjusting canopy light environment F. Li et al. 10.1111/gcb.16503
- Tipping point in North American Arctic-Boreal carbon sink persists in new generation Earth system models despite reduced uncertainty R. Braghiere et al. 10.1088/1748-9326/acb226
- Source-specific light absorption and radiative effects decreases and indications due to the lockdown Y. Qu et al. 10.1016/j.jenvman.2024.120600
- Impact of merging of historical and future climate data sets on land carbon cycle projections for South America C. Huntingford et al. 10.1002/cli2.24
- Enhancing terrestrial net primary productivity estimation with EXP-CASA: A novel light use efficiency model approach G. Chen et al. 10.1016/j.rse.2025.114790
- The impacts of regional transport on anthropogenic source contributions of PM2.5 in a basin city, China H. Liu et al. 10.1016/j.scitotenv.2024.170038
- Characterization of Aerosol and CO2 Co-Emissions around Power Plants through Satellite-Based Synergistic Observations L. Sun et al. 10.3390/rs16091609
- The Importance of Hyperspectral Soil Albedo Information for Improving Earth System Model Projections R. Braghiere et al. 10.1029/2023AV000910
- Progress and challenges in remotely sensed terrestrial carbon fluxes T. Wang et al. 10.1080/10095020.2024.2336599
13 citations as recorded by crossref.
- Legacy Effects Following Fire on Surface Energy, Water and Carbon Fluxes in Mature Amazonian Forests G. de Oliveira et al. 10.1029/2020JG005833
- Drivers of atmospheric CO2 concentration in southeast Brazil: Insights from land use change, vegetation, and climate factors L. da Costa et al. 10.1016/j.rsase.2025.101614
- Microclima no Cenário de Floresta, Pastagem e Cidade no Sudoeste da Amazônia B. Antonucci et al. 10.1590/0102-778640230038
- Aerosol radiative and climatic effects on ecosystem productivity and evapotranspiration H. Zhou et al. 10.1016/j.coesh.2020.10.006
- Vegetation clumping modulates global photosynthesis through adjusting canopy light environment F. Li et al. 10.1111/gcb.16503
- Tipping point in North American Arctic-Boreal carbon sink persists in new generation Earth system models despite reduced uncertainty R. Braghiere et al. 10.1088/1748-9326/acb226
- Source-specific light absorption and radiative effects decreases and indications due to the lockdown Y. Qu et al. 10.1016/j.jenvman.2024.120600
- Impact of merging of historical and future climate data sets on land carbon cycle projections for South America C. Huntingford et al. 10.1002/cli2.24
- Enhancing terrestrial net primary productivity estimation with EXP-CASA: A novel light use efficiency model approach G. Chen et al. 10.1016/j.rse.2025.114790
- The impacts of regional transport on anthropogenic source contributions of PM2.5 in a basin city, China H. Liu et al. 10.1016/j.scitotenv.2024.170038
- Characterization of Aerosol and CO2 Co-Emissions around Power Plants through Satellite-Based Synergistic Observations L. Sun et al. 10.3390/rs16091609
- The Importance of Hyperspectral Soil Albedo Information for Improving Earth System Model Projections R. Braghiere et al. 10.1029/2023AV000910
- Progress and challenges in remotely sensed terrestrial carbon fluxes T. Wang et al. 10.1080/10095020.2024.2336599
Discussed (final revised paper)
Latest update: 29 Jun 2025
Short summary
We evaluate how the interaction of smoke with sun light impacts the exchange of energy and mass between vegetation and the atmosphere using a machine learning technique. We found an effect of the smoke on CO2, energy, and water fluxes, linking the effects of smoke with temperature, humidity, and winds. CO2 exchange increased by up to 55 % in the presence of smoke. A decrease of 12 % was observed for a site with simpler vegetation. Energy fluxes were negatively impacted for all study sites.
We evaluate how the interaction of smoke with sun light impacts the exchange of energy and mass...
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