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Title: A Methodology and Implementation of Automated Emissions Harmonization for Use in Integrated Assessment Models

Abstract

Emissions harmonization refers to the process used to match greenhouse gas (GHG) and air pollutant results from Integrated Assessment Models (IAMs) against a common source of historical emissions. To date, harmonization has been performed separately by individual modeling teams. For the hand-over of emission data for the Shared Socio-economic Pathways (SSPs) to climate model groups, a new automated approach based on commonly agreed upon algorithms was developed. This work describes the novel methodology for determining such harmonization methods and an open-source Python software library implementing the methodology. Results are shown for two example scenarios (with and without climate policy cases) using the MESSAGE-GLOBIOM IAM that satisfactorily harmonize over 96% of the total emissions trajectories while having a negligible eect on key long-term climate indicators. This new capability enhances the comparability across dierent models, increases transparency and robustness of results, and allows other teams to easily participate in intercomparison exercises by using the same, openly available harmonization mechanism.

Authors:
; ORCiD logo; ; ; ; ; ORCiD logo
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1489975
Report Number(s):
PNNL-SA-129400
Journal ID: ISSN 1364-8152
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Environmental Modelling and Software
Additional Journal Information:
Journal Volume: 105; Journal Issue: C; Journal ID: ISSN 1364-8152
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
intergrated assessment, climate change, Harmonization, air pollution

Citation Formats

Gidden, Matthew J., Fujimori, Shinichiro, van den Berg, Maarten, Klein, David, Smith, Steven J., van Vuuren, Detlef P., and Riahi, Keywan. A Methodology and Implementation of Automated Emissions Harmonization for Use in Integrated Assessment Models. United States: N. p., 2018. Web. doi:10.1016/j.envsoft.2018.04.002.
Gidden, Matthew J., Fujimori, Shinichiro, van den Berg, Maarten, Klein, David, Smith, Steven J., van Vuuren, Detlef P., & Riahi, Keywan. A Methodology and Implementation of Automated Emissions Harmonization for Use in Integrated Assessment Models. United States. doi:10.1016/j.envsoft.2018.04.002.
Gidden, Matthew J., Fujimori, Shinichiro, van den Berg, Maarten, Klein, David, Smith, Steven J., van Vuuren, Detlef P., and Riahi, Keywan. Sun . "A Methodology and Implementation of Automated Emissions Harmonization for Use in Integrated Assessment Models". United States. doi:10.1016/j.envsoft.2018.04.002.
@article{osti_1489975,
title = {A Methodology and Implementation of Automated Emissions Harmonization for Use in Integrated Assessment Models},
author = {Gidden, Matthew J. and Fujimori, Shinichiro and van den Berg, Maarten and Klein, David and Smith, Steven J. and van Vuuren, Detlef P. and Riahi, Keywan},
abstractNote = {Emissions harmonization refers to the process used to match greenhouse gas (GHG) and air pollutant results from Integrated Assessment Models (IAMs) against a common source of historical emissions. To date, harmonization has been performed separately by individual modeling teams. For the hand-over of emission data for the Shared Socio-economic Pathways (SSPs) to climate model groups, a new automated approach based on commonly agreed upon algorithms was developed. This work describes the novel methodology for determining such harmonization methods and an open-source Python software library implementing the methodology. Results are shown for two example scenarios (with and without climate policy cases) using the MESSAGE-GLOBIOM IAM that satisfactorily harmonize over 96% of the total emissions trajectories while having a negligible eect on key long-term climate indicators. This new capability enhances the comparability across dierent models, increases transparency and robustness of results, and allows other teams to easily participate in intercomparison exercises by using the same, openly available harmonization mechanism.},
doi = {10.1016/j.envsoft.2018.04.002},
journal = {Environmental Modelling and Software},
issn = {1364-8152},
number = C,
volume = 105,
place = {United States},
year = {2018},
month = {7}
}