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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. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
01/10/2020 |
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Data da última atualização: |
01/10/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
DONKE, A. C. G.; NOVAES, R. M. L.; PAZIANOTTO, R. A. A.; MORENO-RUIZ, E.; REINHARD, J.; PICOLI, J. F.; MATSUURA, M. I. da S. F. |
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Afiliação: |
ANA CRISTINA GUIMARÃES DONKE; RENAN MILAGRES LAGE NOVAES, CNPMA; RICARDO ANTONIO ALMEIDA PAZIANOTTO, CNPMA; EMILIA MORENO-RUIZ, Ecoinvent Association; JÜRGEN REINHARD, Quantis; JULIANA FERREIRA PICOLI; MARILIA IEDA DA S F MATSUURA, CNPMA. |
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Título: |
Integrating regionalized Brazilian land use change datasets into the ecoinvent database: new data, premises and uncertainties have large effects in the results. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
The International Journal of Life Cycle Assessment, v. 25, n. 6, p. 1027-1042, 2020. |
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DOI: |
https://doi.org/10.1007/s11367-020-01763-3 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Purpose: Land use change (LUC) is a critical process in the life cycle greenhouse gas emissions of agricultural products and Brazil is a major exporter of these. This work had the objective of integrating refined and regionalized datasets of LUC in Brazil into the ecoinvent database, to better represent its dynamics and heterogeneity. We present the adaptations needs for having it suitable for crops, pasture and forestry in state-level and impacts of modelling assumptions and uncertainties. Methods Adaptation and integration were based in ecoinvent version 3 guidelines and the database requirements to LUC modelling. BRLUC, a method for Brazilian LUC accounting, was the main data source. The workflow for the integration process consisted in identifying necessary adaptations in both sources to allow a better representation of Brazilian LUC. Four new reference products and 27 geographies were added in the database. Results and discussion A total of 566 new datasets were integrated into ecoinvent version 3.6, allowing the incorporation of LUC in Brazilian products in state, regional and national level. GHG emissions reduced, being 42.2%and 99.9%lower to soybean and sugarcane than in ecoinvent v3.5. Four improvements were the main causes: (i) state-level LUC modelling with national official data; (ii) regionalizing carbon stocks; (iii) including pasture and forestry land use categories; (iv) and considering sugarcane as a perennial crop. The way to calculate national-level results based on subnational data was an important source of difference in emissions too. Uncertainties specifically associated with land use substitution patterns were not incorporated, and they can potentially have impacts as large as the uncertainties of all the remaining processes combined. Conclusions Results showed that small changes in data sources and premises have large impacts on emissions associated with LUC in agricultural products. It also showed the large impacts of uncertainties of LUC patterns. Improving current models in better representing regional LUC patterns, regional carbon stocks and uncertainty accounting could reduce these impacts. Nonetheless, efforts in reducing the complexity of LUC accounting methods could enhance transparency and effectiveness. MenosAbstract: Purpose: Land use change (LUC) is a critical process in the life cycle greenhouse gas emissions of agricultural products and Brazil is a major exporter of these. This work had the objective of integrating refined and regionalized datasets of LUC in Brazil into the ecoinvent database, to better represent its dynamics and heterogeneity. We present the adaptations needs for having it suitable for crops, pasture and forestry in state-level and impacts of modelling assumptions and uncertainties. Methods Adaptation and integration were based in ecoinvent version 3 guidelines and the database requirements to LUC modelling. BRLUC, a method for Brazilian LUC accounting, was the main data source. The workflow for the integration process consisted in identifying necessary adaptations in both sources to allow a better representation of Brazilian LUC. Four new reference products and 27 geographies were added in the database. Results and discussion A total of 566 new datasets were integrated into ecoinvent version 3.6, allowing the incorporation of LUC in Brazilian products in state, regional and national level. GHG emissions reduced, being 42.2%and 99.9%lower to soybean and sugarcane than in ecoinvent v3.5. Four improvements were the main causes: (i) state-level LUC modelling with national official data; (ii) regionalizing carbon stocks; (iii) including pasture and forestry land use categories; (iv) and considering sugarcane as a perennial crop. The way to calculate national-le... Mostrar Tudo |
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Palavras-Chave: |
LUC; Maize; Mato Grosso; Timber. |
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Thesagro: |
Cana de Açúcar; Eucalipto; Gado de Corte; Manga; Milho; Produção Florestal; Soja; Uso da Terra. |
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Thesaurus Nal: |
Beef cattle; Corn; Greenhouse gas emissions; Inventories; Land use change; Mangoes; Plantation forestry; Soybeans; Sugarcane. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 03620naa a2200457 a 4500
001 2125219
005 2020-10-01
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s11367-020-01763-3$2DOI
100 1 $aDONKE, A. C. G.
245 $aIntegrating regionalized Brazilian land use change datasets into the ecoinvent database$bnew data, premises and uncertainties have large effects in the results.$h[electronic resource]
260 $c2020
520 $aAbstract: Purpose: Land use change (LUC) is a critical process in the life cycle greenhouse gas emissions of agricultural products and Brazil is a major exporter of these. This work had the objective of integrating refined and regionalized datasets of LUC in Brazil into the ecoinvent database, to better represent its dynamics and heterogeneity. We present the adaptations needs for having it suitable for crops, pasture and forestry in state-level and impacts of modelling assumptions and uncertainties. Methods Adaptation and integration were based in ecoinvent version 3 guidelines and the database requirements to LUC modelling. BRLUC, a method for Brazilian LUC accounting, was the main data source. The workflow for the integration process consisted in identifying necessary adaptations in both sources to allow a better representation of Brazilian LUC. Four new reference products and 27 geographies were added in the database. Results and discussion A total of 566 new datasets were integrated into ecoinvent version 3.6, allowing the incorporation of LUC in Brazilian products in state, regional and national level. GHG emissions reduced, being 42.2%and 99.9%lower to soybean and sugarcane than in ecoinvent v3.5. Four improvements were the main causes: (i) state-level LUC modelling with national official data; (ii) regionalizing carbon stocks; (iii) including pasture and forestry land use categories; (iv) and considering sugarcane as a perennial crop. The way to calculate national-level results based on subnational data was an important source of difference in emissions too. Uncertainties specifically associated with land use substitution patterns were not incorporated, and they can potentially have impacts as large as the uncertainties of all the remaining processes combined. Conclusions Results showed that small changes in data sources and premises have large impacts on emissions associated with LUC in agricultural products. It also showed the large impacts of uncertainties of LUC patterns. Improving current models in better representing regional LUC patterns, regional carbon stocks and uncertainty accounting could reduce these impacts. Nonetheless, efforts in reducing the complexity of LUC accounting methods could enhance transparency and effectiveness.
650 $aBeef cattle
650 $aCorn
650 $aGreenhouse gas emissions
650 $aInventories
650 $aLand use change
650 $aMangoes
650 $aPlantation forestry
650 $aSoybeans
650 $aSugarcane
650 $aCana de Açúcar
650 $aEucalipto
650 $aGado de Corte
650 $aManga
650 $aMilho
650 $aProdução Florestal
650 $aSoja
650 $aUso da Terra
653 $aLUC
653 $aMaize
653 $aMato Grosso
653 $aTimber
700 1 $aNOVAES, R. M. L.
700 1 $aPAZIANOTTO, R. A. A.
700 1 $aMORENO-RUIZ, E.
700 1 $aREINHARD, J.
700 1 $aPICOLI, J. F.
700 1 $aMATSUURA, M. I. da S. F.
773 $tThe International Journal of Life Cycle Assessment$gv. 25, n. 6, p. 1027-1042, 2020.
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Embrapa Meio Ambiente (CNPMA) |
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| 1. |  | OLIVEIRA, S. P. de; SILVA, R. N. P. da; GOMES, F. da S.; VELARDE, L. G. C.; TEIXEIRA, M. R. M. Fatores determinantes da escolha de frutas, legumes e verduras no município do Rio de Janeiro. Revista da Associação Brasileira de Nutrição, Rio de Janeiro, v. 1, n. 1, p. 134, maio/jul. 2008. Edição dos Anais do XX Congresso Brasileiro de Nutrição, Rio de Janeiro, maio 2008.| Tipo: Resumo em Anais de Congresso |
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