A multiple-uncertainty analysis framework for integrated assessment modelling of several sustainable development goals. (September 2020)

• Record Type: Journal Article
• Authors: Forouli, Aikaterini; Nikas, Alexandros; Van de Ven, Dirk-Jan; Sampedro, Jon; Doukas, Haris
• Is Part Of: Environmental modelling & software. Volume 131(2020)
• Publication Date: 2020-09
• Subjects: Integrated assessment modeling -- Global change assessment model -- Shared socioeconomic pathways -- Sustainable development goals -- Stochastic uncertainty -- Scenario analysis; 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.2020.104795
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: This research introduces a two-level integration of climate-economy modelling and portfolio analysis, to simulate technological subsidisation with implications for multiple Sustainable Development Goals (SDGs), across socioeconomic trajectories and considering different levels of uncertainties. We use integrated assessment modelling outputs relevant for progress across three SDGs—namely air pollution-related mortality (SDG3), access to clean energy (SDG7) and greenhouse gas emissions (SDG13)—calculated with the Global Change Assessment Model (GCAM) for different subsidy levels for six sustainable technologies, across three Shared Socioeconomic Pathways (SSPs), feeding them into a portfolio analysis model. Optimal portfolios that are robust in the individual socioeconomic scenarios as well as across the socioeconomic scenarios are identified, by means of an SSP-robustness score. A second link between the two models is established, by feeding portfolio analysis results back into GCAM. Application in a case study for Eastern Africa confirms that most SSP-robust portfolios show smaller output ranges among scenarios. Highlights: An integrated assessment model is linked to a portfolio analysis model in two stages. Technological subsidisation is modelled in different shared socioeconomic pathways. Impacts on health, energy access and resulting emissions are considered uncertain. We create a midpoint dataset and analyse uncertainty across the broad scenario range. For validation, the most robust technological portfolios are simulated again in GCAM.