SEEG initiative estimates of Brazilian greenhouse gas emissions from 1970 to 2015

This work presents the SEEG platform, a 46-year long dataset of greenhouse gas emissions (GHG) in Brazil (1970–2015) providing more than 2 million data records for the Agriculture, Energy, Industry, Waste and Land Use Change Sectors at national and subnational levels. The SEEG dataset was developed...

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Veröffentlicht in:Scientific data 2018-05, Vol.5 (1), p.180045-180045, Article 180045
Hauptverfasser: de Azevedo, Tasso Rezende, Costa Junior, Ciniro, Brandão Junior, Amintas, Cremer, Marcelo dos Santos, Piatto, Marina, Tsai, David Shiling, Barreto, Paulo, Martins, Heron, Sales, Márcio, Galuchi, Tharic, Rodrigues, Alessandro, Morgado, Renato, Ferreira, André Luis, Barcellos e Silva, Felipe, Viscondi, Gabriel de Freitas, dos Santos, Karoline Costal, Cunha, Kamyla Borges da, Manetti, Andrea, Coluna, Iris Moura Esteves, Albuquerque, Igor Reis de, Junior, Shigueo Watanabe, Leite, Clauber, Kishinami, Roberto
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Sprache:eng
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Zusammenfassung:This work presents the SEEG platform, a 46-year long dataset of greenhouse gas emissions (GHG) in Brazil (1970–2015) providing more than 2 million data records for the Agriculture, Energy, Industry, Waste and Land Use Change Sectors at national and subnational levels. The SEEG dataset was developed by the Climate Observatory, a Brazilian civil society initiative, based on the IPCC guidelines and Brazilian National Inventories embedded with country specific emission factors and processes, raw data from multiple official and non-official sources, and organized together with social and economic indicators. Once completed, the SEEG dataset was converted into a spreadsheet format and shared via web-platform that, by means of simple queries, allows users to search data by emission sources and country and state activities. Because of its effectiveness in producing and making available data on a consistent and accessible basis, SEEG may significantly increase the capacity of civil society, scientists and stakeholders to understand and anticipate trends related to GHG emissions as well as its implications to public policies in Brazil. Design Type(s) data integration objective • source-based data transformation objective Measurement Type(s) gas emission process Technology Type(s) computational modeling technique Factor Type(s) greenhouse gas Sample Characteristic(s) Brazil • methane • dinitrogen oxide • carbon dioxide • carbon monoxide • volatile organic compound • nitrogen oxide • fluorocarbon • fluorohydrocarbon • sulfur hexafluoride Machine-accessible metadata file describing the reported data (ISA-Tab format)
ISSN:2052-4463
2052-4463
DOI:10.1038/sdata.2018.45