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Uncertainty of Consumption-Based Carbon Accounts
[Image: see text] Consumption-based carbon accounts (CBCAs) track how final demand in a region causes carbon emissions elsewhere due to supply chains in the global economic network, taking into account international trade. Despite the importance of CBCAs as an approach for understanding and quantify...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical Society
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6150677/ https://www.ncbi.nlm.nih.gov/pubmed/29897752 http://dx.doi.org/10.1021/acs.est.8b00632 |
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author | Rodrigues, João F. D. Moran, Daniel Wood, Richard Behrens, Paul |
author_facet | Rodrigues, João F. D. Moran, Daniel Wood, Richard Behrens, Paul |
author_sort | Rodrigues, João F. D. |
collection | PubMed |
description | [Image: see text] Consumption-based carbon accounts (CBCAs) track how final demand in a region causes carbon emissions elsewhere due to supply chains in the global economic network, taking into account international trade. Despite the importance of CBCAs as an approach for understanding and quantifying responsibilities in climate mitigation efforts, very little is known of their uncertainties. Here we use five global multiregional input-output (MRIO) databases to empirically calibrate a stochastic multivariate model of the global economy and its GHG emissions in order to identify the main drivers of uncertainty in global CBCAs. We find that the uncertainty of country CBCAs varies between 2 and 16% and that the uncertainty of emissions does not decrease significantly with their size. We find that the bias of ignoring correlations in the data (that is, independent sampling) is significant, with uncertainties being systematically underestimated. We find that both CBCAs and source MRIO tables exhibit strong correlations between the sector-level data of different countries. Finally, we find that the largest contributors to global CBCA uncertainty are the electricity sector data globally and Chinese national data in particular. We anticipate that this work will provide practitioners an approach to understand CBCA uncertainties and researchers compiling MRIOs a guide to prioritize uncertainty reduction efforts. |
format | Online Article Text |
id | pubmed-6150677 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American
Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-61506772018-09-24 Uncertainty of Consumption-Based Carbon Accounts Rodrigues, João F. D. Moran, Daniel Wood, Richard Behrens, Paul Environ Sci Technol [Image: see text] Consumption-based carbon accounts (CBCAs) track how final demand in a region causes carbon emissions elsewhere due to supply chains in the global economic network, taking into account international trade. Despite the importance of CBCAs as an approach for understanding and quantifying responsibilities in climate mitigation efforts, very little is known of their uncertainties. Here we use five global multiregional input-output (MRIO) databases to empirically calibrate a stochastic multivariate model of the global economy and its GHG emissions in order to identify the main drivers of uncertainty in global CBCAs. We find that the uncertainty of country CBCAs varies between 2 and 16% and that the uncertainty of emissions does not decrease significantly with their size. We find that the bias of ignoring correlations in the data (that is, independent sampling) is significant, with uncertainties being systematically underestimated. We find that both CBCAs and source MRIO tables exhibit strong correlations between the sector-level data of different countries. Finally, we find that the largest contributors to global CBCA uncertainty are the electricity sector data globally and Chinese national data in particular. We anticipate that this work will provide practitioners an approach to understand CBCA uncertainties and researchers compiling MRIOs a guide to prioritize uncertainty reduction efforts. American Chemical Society 2018-06-13 2018-07-03 /pmc/articles/PMC6150677/ /pubmed/29897752 http://dx.doi.org/10.1021/acs.est.8b00632 Text en Copyright © 2018 American Chemical Society This is an open access article published under a Creative Commons Non-Commercial No Derivative Works (CC-BY-NC-ND) Attribution License (http://pubs.acs.org/page/policy/authorchoice_ccbyncnd_termsofuse.html) , which permits copying and redistribution of the article, and creation of adaptations, all for non-commercial purposes. |
spellingShingle | Rodrigues, João F. D. Moran, Daniel Wood, Richard Behrens, Paul Uncertainty of Consumption-Based Carbon Accounts |
title | Uncertainty
of Consumption-Based Carbon Accounts |
title_full | Uncertainty
of Consumption-Based Carbon Accounts |
title_fullStr | Uncertainty
of Consumption-Based Carbon Accounts |
title_full_unstemmed | Uncertainty
of Consumption-Based Carbon Accounts |
title_short | Uncertainty
of Consumption-Based Carbon Accounts |
title_sort | uncertainty
of consumption-based carbon accounts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6150677/ https://www.ncbi.nlm.nih.gov/pubmed/29897752 http://dx.doi.org/10.1021/acs.est.8b00632 |
work_keys_str_mv | AT rodriguesjoaofd uncertaintyofconsumptionbasedcarbonaccounts AT morandaniel uncertaintyofconsumptionbasedcarbonaccounts AT woodrichard uncertaintyofconsumptionbasedcarbonaccounts AT behrenspaul uncertaintyofconsumptionbasedcarbonaccounts |