dc.contributor.author | Wiebe, Kirsten Svenja | |
dc.date.accessioned | 2019-03-20T14:23:05Z | |
dc.date.available | 2019-03-20T14:23:05Z | |
dc.date.created | 2018-05-19T10:43:59Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Journal of Cleaner Production. 2018, 194 243-252. | nb_NO |
dc.identifier.issn | 0959-6526 | |
dc.identifier.uri | http://hdl.handle.net/11250/2590907 | |
dc.description.abstract | Data on consumption-based CO2 emissions has become increasingly available over the past years. These data raise the awareness of the link between final goods and the environmental pollution caused by upstream production processes. Consumers of final products learn where in the world CO2 was emitted along the upstream production chain. For producers of final products these data provide benchmarks for total CO2 emitted in upstream production processes. These are used together with an extended version of the inverse important coefficient methodology to identify ‘emission hotspots’. ‘Emission hotspots’ are defined as countries/industries where a bulk of the upstream emissions occur and where a change in technology brings about the largest decrease in upstream emissions. This knowledge provides a basis for well-targeted technology transfers to clean up the upstream production chain, thus reducing the emission footprint of final goods production. The highest impact overall in a significant number global value chains analyzed here would be replacing upstream use of coal electricity by low carbon electricity. These results support the call of the ‘Powering Past Coal Alliance’ at the COP23 of ending the use of coal power sooner rather than later. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Elsevier | nb_NO |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Identifying emission hotspots for low carbon technology transfers | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.pagenumber | 243-252 | nb_NO |
dc.source.volume | 194 | nb_NO |
dc.source.journal | Journal of Cleaner Production | nb_NO |
dc.identifier.doi | 10.1016/j.jclepro.2018.05.003 | |
dc.identifier.cristin | 1585655 | |
dc.description.localcode | © 2018. This is the authors’ accepted and refereed manuscript to the article. Locked until 17.5.2020 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | nb_NO |
cristin.unitcode | 194,64,25,0 | |
cristin.unitname | Institutt for energi- og prosessteknikk | |
cristin.ispublished | true | |
cristin.fulltext | preprint | |
cristin.qualitycode | 2 | |