02 Jan 2024
 | 02 Jan 2024
Status: this preprint is currently under review for the journal ESSD.

Estimating the uncertainty of the greenhouse gas emission accounts in Global Multi-Regional Input-Output analysis

Simon Schulte, Arthur Jakobs, and Stefan Pauliuk

Abstract. Global multi-regional input-output (GMRIO) analysis is the standard tool to calculate consumption-based carbon accounts at the macro level. Recent inter-database comparisons have exposed discrepancies in GMRIO-based results, pinpointing greenhouse gas (GHG) emission accounts as the primary source of variation. A few studies have delved into the robustness of GHG emission accounts, using Monte-Carlo simulations to understand how uncertainty from raw data propagates to the final GHG emission accounts. However, these studies often make simplistic assumptions about raw data uncertainty and ignore correlations between disaggregated variables.

Here, we compile GHG emission accounts for the year 2015 according to the resolution of EXIOBASE v3, covering CO2, CH4 and N2O emissions. We propagate uncertainty from the raw data, namely the United Nations Framework Convention on Climate Change (UNFCCC) and EDGAR inventories, to the GHG emission accounts, and then further to the GHG footprints. We address both limitations from previous studies. First, instead of making simplistic assumptions, we utilise authoritative raw data uncertainty estimates from the National Inventory Reports (NIR) submitted to the UNFCCC and a recent study on uncertainty of the EDGAR emission inventory. Second, we account for inherent correlations due to data disaggregation by sampling from a Dirichlet distribution.

Our results show a median coefficient of variation (CV) for GHG emission accounts at the country level of 4 % for CO2, 12 % for CH4, and 33 % for N2O. For CO2, smaller economies with significant international aviation or shipping sectors show CVs as high as 94 %, as seen in Malta. At the sector level, uncertainties are higher, with median CVs of 94 % for CO2, 100 % for CH4, and 113 % for N2O. Overall, uncertainty decreases when propagated from GHG emission accounts to GHG footprints, likely due to the cancelling out effects caused by the distribution of emissions and their uncertainties across global supply chains. Our GHG emission accounts generally align with official EXIOBASE emission accounts and OECD data at the country level, though discrepancies at the sectoral level give cause for further examination.

We provide our GHG emission accounts with associated uncertainties and correlations at (Schulte et al. 2023) to complement the official EXIOBASE emission accounts for users interested in estimating the uncertainties of their results.

Simon Schulte, Arthur Jakobs, and Stefan Pauliuk

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-473', Anonymous Referee #1, 13 Feb 2024
    • AC1: 'Reply on RC1', Simon Schulte, 19 Feb 2024
  • RC2: 'Comment on essd-2023-473', Anonymous Referee #2, 19 Feb 2024
Simon Schulte, Arthur Jakobs, and Stefan Pauliuk

Data sets

Uncertainty of EXIOBASE GHG emission acounts 2015 Simon Schulte, Arthur Jakobs, and Stefan Pauliuk

Uncertainties from the UNFCCC National Inventory Reports (submission 2017) Simon Schulte and Joshua Heipel

Correspondence table between UNFCCC CRF and EXIOBASE industry sectors Simon Schulte

Model code and software

Code for estimating the uncertainty of EXIOBASE GHG emissions accounts Simon Schulte

Simon Schulte, Arthur Jakobs, and Stefan Pauliuk


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Short summary
Greenhouse gas (GHG) emissions accounts record emissions according to the economic boundary of a country, irrespective of whether they occur within the national borders or not. In this study, we explore the accuracy of those GHG emission accounts. We find that the accuracy varies significantly depending on the country and economic sector. For example, small countries with extensive aviation or shipping activities show a high degree of uncertainty in their GHG emission accounts.