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| 5. |  | DALLA COSTA, O. A.; MIRANDA, C. R. de; ATHAYDE, N. B.; ARAÚJO, A. P.; CIOCCA, J. R. P.; BALBINOTT, L.; ARBORTE, C.; ROÇA, R. O. Fatores que influenciam a taxa de mortalidade dos suínos durante o manejo pré-abate: uma visão de produtores, transportadores e técnicos. In: CONGRESSO BRASILEIRO DE MEDICINA VETERINÁRIA, 35., 2008, Gramado. Anais. Gramado: SMVZ, 2008. Projeto/Plano de Ação: 02.06.10100-04. Acesso em 28 out. 2008.| Biblioteca(s): Embrapa Suínos e Aves. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Meio Ambiente. Para informações adicionais entre em contato com cnpma.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
21/07/2022 |
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Data da última atualização: |
21/07/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
GAROFALO, D. F. T.; NOVAES, R. M. L.; PAZIANOTTO, R. A. A.; MACIEL, V. G.; BRANDÃO, M.; SHIMBO, J. Z.; MATSUURA, M. I. da S. F. |
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Afiliação: |
DANILO FRANCISCO TROVO GAROFALO; RENAN MILAGRES LAGE NOVAES, CNPMA; RICARDO ANTONIO ALMEIDA PAZIANOTTO, CNPMA; VINÍCIUS GONÇALVES MACIEL; MIGUEL BRANDÃO, KTH Royal Institute of Technology; JULIA ZANIN SHIMBO, Instituto de Pesquisa Ambiental da Amazônia; MARILIA IEDA DA S F MATSUURA, CNPMA. |
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Título: |
Land-use change CO2 emissions associated with agricultural products at municipal level in Brazil. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Journal of Cleaner Production, v. 364, article 132549, 2022. |
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ISSN: |
0959-6526 |
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DOI: |
https://doi.org/10.1016/j.jclepro.2022.13254 |
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Idioma: |
Inglês |
|
Conteúdo: |
Abstract: Land-use change (LUC) accounted for approximately 66% of CO2 emissions in Brazil in 2020, with significant implications for carbon footprint of Brazilian agricultural products. Accurate LUC estimates associated with agriculture are critical to carbon footprint (CF) and life cycle assessment (LCA) studies and derived measures towards low-carbon supply chains. The aim of the study was to provide direct LUC (dLUC) estimates of CO2 emissions associated with a comprehensive set of agricultural products in Brazil at municipal-level and based on spatially-explicit land conversion data, appropriate for CF and LCA studies. The effect of different dLUC modeling choices on the results are also presented. The modeling followed IPCC guidelines and improved the BRLUC method. MapBiomas spatially-explicit data, municipality-level statistics, regionalized carbon stocks and a shared responsibility approach were combined to obtain dLUC emission rates for 64 crops, plus forestry and planted pastures, in the 5,570 Brazilian municipalities, as well as at state and national levels. It will be open access at www.embrapa.br. The most recent version led to an estimated 911 Mtons of CO2 associated with agriculture in 2019, 81% of that associated with planted pastures. National level dLUC emission rates for corn, pastures, soybean and sugarcane were estimated as 2.0, 4.1, 2.3 and 0.3 tCO2.ha?1.yr?1, respectively. The dLUC emissions are highly heterogeneous across the country and land uses, ranging from positive to negative. In general, they were higher in the Amazon biome, due to deforestation, and lower in Eastern Brazil, where agricultural areas are more consolidated. The resulting data is more consistent with dLUC rationale, IPCC guidelines and PAS2050 when previous land use is known and is recommended to be used, whenever data at farm level are not available. The study also shows the strong effect of different dLUC modeling choices on results and reinforces recommendations for further mitigation options. MenosAbstract: Land-use change (LUC) accounted for approximately 66% of CO2 emissions in Brazil in 2020, with significant implications for carbon footprint of Brazilian agricultural products. Accurate LUC estimates associated with agriculture are critical to carbon footprint (CF) and life cycle assessment (LCA) studies and derived measures towards low-carbon supply chains. The aim of the study was to provide direct LUC (dLUC) estimates of CO2 emissions associated with a comprehensive set of agricultural products in Brazil at municipal-level and based on spatially-explicit land conversion data, appropriate for CF and LCA studies. The effect of different dLUC modeling choices on the results are also presented. The modeling followed IPCC guidelines and improved the BRLUC method. MapBiomas spatially-explicit data, municipality-level statistics, regionalized carbon stocks and a shared responsibility approach were combined to obtain dLUC emission rates for 64 crops, plus forestry and planted pastures, in the 5,570 Brazilian municipalities, as well as at state and national levels. It will be open access at www.embrapa.br. The most recent version led to an estimated 911 Mtons of CO2 associated with agriculture in 2019, 81% of that associated with planted pastures. National level dLUC emission rates for corn, pastures, soybean and sugarcane were estimated as 2.0, 4.1, 2.3 and 0.3 tCO2.ha?1.yr?1, respectively. The dLUC emissions are highly heterogeneous across the country and land uses, ra... Mostrar Tudo |
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Palavras-Chave: |
BRLUC method; Land occupation; Land transformation; Product environmental footprint. |
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Thesagro: |
Agricultura; Cana de Açúcar; Impacto Ambiental; Pastagem; Produção Agrícola; Soja; Uso da Terra. |
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Thesaurus NAL: |
Bioenergy; Biofuels; Carbon footprint; Land use change; Pastures; Soybeans. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 03244naa a2200421 a 4500
001 2144859
005 2022-07-21
008 2022 bl uuuu u00u1 u #d
022 $a0959-6526
024 7 $ahttps://doi.org/10.1016/j.jclepro.2022.13254$2DOI
100 1 $aGAROFALO, D. F. T.
245 $aLand-use change CO2 emissions associated with agricultural products at municipal level in Brazil.$h[electronic resource]
260 $c2022
520 $aAbstract: Land-use change (LUC) accounted for approximately 66% of CO2 emissions in Brazil in 2020, with significant implications for carbon footprint of Brazilian agricultural products. Accurate LUC estimates associated with agriculture are critical to carbon footprint (CF) and life cycle assessment (LCA) studies and derived measures towards low-carbon supply chains. The aim of the study was to provide direct LUC (dLUC) estimates of CO2 emissions associated with a comprehensive set of agricultural products in Brazil at municipal-level and based on spatially-explicit land conversion data, appropriate for CF and LCA studies. The effect of different dLUC modeling choices on the results are also presented. The modeling followed IPCC guidelines and improved the BRLUC method. MapBiomas spatially-explicit data, municipality-level statistics, regionalized carbon stocks and a shared responsibility approach were combined to obtain dLUC emission rates for 64 crops, plus forestry and planted pastures, in the 5,570 Brazilian municipalities, as well as at state and national levels. It will be open access at www.embrapa.br. The most recent version led to an estimated 911 Mtons of CO2 associated with agriculture in 2019, 81% of that associated with planted pastures. National level dLUC emission rates for corn, pastures, soybean and sugarcane were estimated as 2.0, 4.1, 2.3 and 0.3 tCO2.ha?1.yr?1, respectively. The dLUC emissions are highly heterogeneous across the country and land uses, ranging from positive to negative. In general, they were higher in the Amazon biome, due to deforestation, and lower in Eastern Brazil, where agricultural areas are more consolidated. The resulting data is more consistent with dLUC rationale, IPCC guidelines and PAS2050 when previous land use is known and is recommended to be used, whenever data at farm level are not available. The study also shows the strong effect of different dLUC modeling choices on results and reinforces recommendations for further mitigation options.
650 $aBioenergy
650 $aBiofuels
650 $aCarbon footprint
650 $aLand use change
650 $aPastures
650 $aSoybeans
650 $aAgricultura
650 $aCana de Açúcar
650 $aImpacto Ambiental
650 $aPastagem
650 $aProdução Agrícola
650 $aSoja
650 $aUso da Terra
653 $aBRLUC method
653 $aLand occupation
653 $aLand transformation
653 $aProduct environmental footprint
700 1 $aNOVAES, R. M. L.
700 1 $aPAZIANOTTO, R. A. A.
700 1 $aMACIEL, V. G.
700 1 $aBRANDÃO, M.
700 1 $aSHIMBO, J. Z.
700 1 $aMATSUURA, M. I. da S. F.
773 $tJournal of Cleaner Production$gv. 364, article 132549, 2022.
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