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Cited by 103Environmental Impact and SustainabilitySustainability and Ecological Systems AnalysisClimate Change Policy and Economics

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Uncertainty of Consumption-Based Carbon Accounts

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Rodrigues, João F. D., Moran, Daniel, Wood, Richard, Behrens, Paul·2018·Environmental Science & Technology
DOI 10.1021/acs.est.8b00632PMC PMC6150677
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Abstract

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.

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Metadata

Authors
Rodrigues, J. F. D., Moran, D., Wood, R., & Behrens, P.
Affiliations
  • Leiden University , , Einsteinweg 2 , ,
  • Norwegian University of Science and Technology (NO)
  • Leiden University (NL)
ORCID
Venue
Environmental Science & Technology
Publisher
American Chemical Society (ACS)
Published
2018-06-13
Volume
52
Issue
13
Pages
7577-7586
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
DOI
10.1021/acs.est.8b00632
PMC
PMC6150677
OpenAlex
W2807914698
Cited by
103
References
0
Citations by year
2026: 12 · 2025: 11 · 2024: 6 · 2023: 10 · 2022: 9 · 2021: 13 · 2020: 22 · 2019: 14 · 2018: 5
FWCI
6.78
Type
journal article
Language
en
Open access
Licence
Locations
  • Environmental Science & Technology (publishedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Leiden Repository (Leiden University) (submittedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc-nd)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
  • FP7 Environment (603386)
  • Naturvårdsverket (NA)
Topics
  • Physical Sciences › Environmental Science › Environmental Engineering › Environmental Impact and Sustainability
  • Physical Sciences › Environmental Science › Environmental Engineering › Sustainability and Ecological Systems Analysis
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
Keywords
uncertainty, multi-regional input-output tables, global supply chains, international trade, greenhouse gas emissions, sampling bias, electric utilities, China
MeSH terms
Carbon, Uncertainty, Carbon Footprint

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