Scientific Software

The Energy Program is developing a suite of tools and scientific software packages to facilitate the analysis of climate-change mitigation scenarios in the context of sustainable development.

Screenshot from the IAMC 1.5°C Scenario Explorer hosted by IIASA (https://data.ene.iiasa.ac.at/iamc-1.5c-explorer)

Screenshot from the IAMC 1.5°C Scenario Explorer hosted by IIASA (https://data.ene.iiasa.ac.at/iamc-1.5c-explorer)

The open-source MESSAGEix framework and the ixmp package for scenario data management

MESSAGEix is a versatile and flexible framework that can be used to develop and run a broad range of energy system models, taking into account emissions, environmental dimenions and a variety of sustainable-development indicators. Applications of the MESSAGEix framework can range from very stylized national exercises to the global MESSAGEix-GLOBIOM integrated-assessment model, which is described in detail here.

The MESSAGEix framework is fully integrated with IIASA’s ix modeling platform (ixmp), a data warehouse for high-powered numerical scenario analysis. The platform supports an efficient workflow between original input data sources, the implementation of the mathematical model formulation, and the analysis of numerical results. The platform can be accessed via a web-based user interface and application programming interfaces (API) to the scientific programming languages Python and R. The platform also includes a generic data exchange API to GAMS for numerical computation.

More information: https://docs.messageix.org

The Scenario Explorer and ixmp server infrastructure

The Scenario Explorer is a web-based user interface to access and manage scenario data. It provides intuitive visualizations and display of timeseries data and download of the data in multiple formats.

 The Scenario Explorer also has an interface for uploading and managing scenario data as a central data repository in multi-institution model comparison exercises. The infrastructure includes data version control and allows to execute scenario post-processing on any uploaded data (e.g., validation, consistency, meta-analysis).

 More information: https://software.ene.iiasa.ac.at/ixmp-server

pyam: Open-source Python Package for Scenario Analysis and Visualization

This package provides a suite of tools and functions for analyzing and visualizing input data (i.e., assumptions, parametrization) and results (model output) of integrated-assessment scenarios, energy systems analysis, and sectoral studies.

The package is based on the timeseries data format developed by the Integrated Assessment Modeling Consortium (IAMC), but it supports additional features such as sub-annual time resolution.

Documentation: pyam-iamc.readthedocs.io
GitHub repository: github.com/IAMconsortium/pyam
Community forum: pyam.groups.io

iam-units: Open-source Python Package for Common Unit Conversion in Integrated-assessment Research

This package provides a simple and intuitive way to convert units frequently used in research on integrated assessment, energy systems research, climate change mitigation and sustainable development. It includes conversion of greenhouse gas species to carbon-dioxide equivalent using any Global Warming Potential (GWP) factors determined in recent IPCC assessment reports.

GitHub repository: github.com/IAMconsortium/units





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Last edited: 08 September 2020

CONTACT DETAILS

Daniel Huppmann

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Integrated Assessment and Climate Change Research Group

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Integrated Assessment and Climate Change Research Group|Sustainable Service Systems Research Group

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Energy

Climate

and Environment Program

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Software

https://software.ene.iiasa.ac.at/

PUBLICATIONS

Zhong, H., Feng, K., Sun, L., Tian, Z., Fischer, G., Cheng, L., & Munoz Castillo, R. (2021). Water-land tradeoffs to meet future demands for sugar crops in Latin America and the Caribbean: A bio-physical and socio-economic nexus perspective. Resources, Conservation and Recycling 169, e105510. 10.1016/j.resconrec.2021.105510.

Kofner, Y. & Erokhin, D. (2021). EU – EAEU Common Economic Space. In: The Routledge Handbook of EU-Russia Relations: Structures, Actors, Issues. Eds. Romanova, T. & David, M., Routledge. ISBN 9781138543676

Gao, J., Xu, X., Cao, G.-Y., Ermoliev, Y., Ermolieva, T., & Rovenskaya, E. (2021). Strategic decision-support modeling for robust management of the food–energy–water nexus under uncertainty. Journal of Cleaner Production 292, e125995. 10.1016/j.jclepro.2021.125995.

Jie, D., Xu, X., & Guo, F. (2021). The future of coal supply in China based on non-fossil energy development and carbon price strategies. Energy 220, e119644. 10.1016/j.energy.2020.119644.

Escobar Lanzuela, N. & Britz, W. (2021). Metrics on the sustainability of region-specific bioplastics production, considering global land use change effects. Resources, Conservation and Recycling 167, e105345.

Ruane, A.C., Phillips, M., Müller, C., Elliott, J., Jägermeyr, J., Arneth, A., Balkovič, J. , Deryng, D., et al. (2021). Strong regional influence of climatic forcing datasets on global crop model ensembles. Agricultural and Forest Meteorology 300, e108313. 10.1016/j.agrformet.2020.108313.

Stenzel, F., Greve, P., Lucht, W., Tramberend, S. , Wada, Y. , & Gerten, D. (2021). Irrigation of biomass plantations may globally increase water stress more than climate change. Nature Communications 12 (1), e1512. 10.1038/s41467-021-21640-3.

Repka, S., Erkkilä-Välimäki, A., Jonson, J.E., Posch, M. , Törrönen, J., & Jalkanen, J.P. (2021). Assessing the costs and environmental benefits of IMO regulations of ship-originated SOx and NOx emissions in the Baltic Sea. Ambio 10.1007/s13280-021-01500-6.

Vasilev, Y., Cherepovitsyn, A., Tsvetkova, A., & Komendantova, N. (2021). Promoting Public Awareness of Carbon Capture and Storage Technologies in the Russian Federation: A System of Educational Activities. Energies 14 (5) 10.3390/ en14051408.

Dianati, K., Schäfer, L., Milner, J., Gomez Sanabria, A. , Gitau, H., Hale, J., Langmaack, H., Kiesewetter, G., et al. (2021). A System Dynamics-based Scenario Analysis of Residential Solid Waste Management in Kisumu, Kenya. Science of the Total Environment, e146200. 10.1016/j.scitotenv.2021.146200. (In Press)

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