@Article{TejadaPinelGBCSMMAGMCDSCCNV:2023:ArBoEs,
               author = "Tejada Pinel, Graciela and Gatti, Luciana Vanni and Basso, Luana 
                         Santamaria and Cassol, Henrique Lu{\'{\i}}s Godinho and Silva 
                         J{\'u}nior, Celso Henrique Leite and Mataveli, Guilherme Augusto 
                         Verola and Marani, Luciano and Arai, Egidio and Gloor, Manuel and 
                         Miller, John B. and Cunha, Camilla Lima and Domingues, Lucas Gatti 
                         and Sanchez Ipia, Alber Hamersson and Correia, Caio Silvestre de 
                         Carvalho and Crispim, St{\'e}phane Palma and Neves, Raiane 
                         Aparecida Lopes and Von Randow, Celso",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas da 
                         Amaz{\^o}nia (INPA)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {University of Leeds} and {National Oceanic and Atmospheric 
                         Administration (NOAA)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "CO2 emissions in the Amazon: are bottom-up estimates from land use 
                         and cover datasets consistent with top-down estimates based on 
                         atmospheric measurements?",
              journal = "Frontiers in Forests and Global Change",
                 year = "2023",
               volume = "6",
                pages = "e1107580",
             keywords = "Amazon, bottom-up top-down approaches, CO2 atmospheric 
                         measurements, CO2 emissions, emission factors, land use and cover 
                         change.",
             abstract = "Amazon forests are the largest forests in the tropics and play a 
                         fundamental role for regional and global ecosystem service 
                         provision. However, they are under threat primarily from 
                         deforestation. Amazonia's carbon balance trend reflects the 
                         condition of its forests. There are different approaches to 
                         estimate large-scale carbon balances, including top-down (e.g., 
                         CO2 atmospheric measurements combined with atmospheric transport 
                         information) and bottom-up (e.g., land use and cover change (LUCC) 
                         data based on remote sensing methods). It is important to 
                         understand their similarities and differences. Here we provide 
                         bottom-up LUCC estimates and determine to what extent they are 
                         consistent with recent top-down flux estimates during 2010 to 2018 
                         for the Brazilian Amazon. We combine LUCC datasets resulting in 
                         annual LUCC maps from 2010 to 2018 with emissions and removals for 
                         each LUCC, and compare the resulting CO2 estimates with top-down 
                         estimates based on atmospheric measurements. We take into account 
                         forest carbon stock maps for estimating loss processes, and carbon 
                         uptake of regenerating and mature forests. In the bottom-up 
                         approach total CO2 emissions (2010 to 2018), deforestation and 
                         degradation are the largest contributing processes accounting for 
                         58% (4.3 PgCO2) and 37% (2.7 PgCO2) respectively. Looking at the 
                         total carbon uptake, primary forests play a dominant role 
                         accounting for 79% (\−5.9 PgCO2) and secondary forest 
                         growth for 17% (\−1.2 PgCO2). Overall, according to our 
                         bottom-up estimates the Brazilian Amazon is a carbon sink until 
                         2014 and a source from 2015 to 2018. In contrast according to the 
                         top-down approach the Brazilian Amazon is a source during the 
                         entire period. Both approaches estimate largest emissions in 2016. 
                         During the period where flux signs are the same (20152018) 
                         top-down estimates are approximately 3 times larger in 20152016 
                         than bottom-up estimates while in 20172018 there is closer 
                         agreement. There is some agreement between the approachesnotably 
                         that the Brazilian Amazon has been a source during 20152018 
                         however there are also disagreements. Generally, emissions 
                         estimated by the bottom-up approach tend to be lower. 
                         Understanding the differences will help improve both approaches 
                         and our understanding of the Amazon carbon cycle under human 
                         pressure and climate change.",
                  doi = "10.3389/ffgc.2023.1107580",
                  url = "http://dx.doi.org/10.3389/ffgc.2023.1107580",
                 issn = "2624-893X",
                label = "self-archiving-INPE-MCTIC-GOV-BR",
             language = "en",
           targetfile = "ffgc-06-1107580.pdf",
        urlaccessdate = "15 jun. 2024"
}