A methodology and implementation of automated emissions harmonization for use in Integrated Assessment Models. (July 2018)

• Record Type: Journal Article
• Authors: Gidden, Matthew J.; Fujimori, Shinichiro; van den Berg, Maarten; Klein, David; Smith, Steven J.; van Vuuren, Detlef P.; Riahi, Keywan
• Is Part Of: Environmental modelling & software. Volume 105(2018)
• Page Start: 187
• Page End: 200
• Publication Date: 2018-07
• Subjects: Integrated assessment models -- Harmonization -- Greenhouse gases (GHGs) -- Air pollution; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.04.002
• Languages: English
• ISSNs: 1364-8152

Abstract

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 Socioeconomic 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. A case study is presented for two example scenarios (with and without climate policy cases) using the IAM MESSAGE-GLOBIOM that satisfactorily harmonize over 96% of the total emissions trajectories while having a negligible effect on key long-term climate indicators. This new capability enhances the comparability across different 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. Highlights: A novel methodology for the automated harmonization with a common historical data set of generic emissions trajectories of Integrated Assessment Models (IAMs) is proposed. A framework and open-source software implementation of the methodology is described. Two scenarios from the Shared Socioeconomic Pathways (SSPs) are harmonized and proof-of-concept results are presented. Over 96% of the approximately 2000 emissions trajectories are shown to be successfully harmonized without the need for further review. Common situations in which additional review is required (4% of trajectories in this study) are presented and solutions are suggested.