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: 25 March 2021

CONTACT DETAILS

Daniel Huppmann

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Integrated Assessment and Climate Change Research Group

Energy, Climate, and Environment Program

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Volker Krey

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Energy, Climate, and Environment Program

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Sustainable Service Systems Research Group

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Energy, Climate, and Environment Program

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Pollution Management Research Group

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Energy, Climate, and Environment Program

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Software

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

PUBLICATIONS

Hunt, J. , Zakeri, B. , de Barros, A.G., Filho, W.L., Marques, A.D., Barbosa, P.S.F., Schneider, P.S., & Farenzena, M. (2021). Buoyancy Energy Storage Technology: An energy storage solution for islands, coastal regions, offshore wind power and hydrogen compression. Journal of Energy Storage 40, e102746. 10.1016/j.est.2021.102746.

Oshiro, K., Fujimori, S. , Ochi, Y., & Ehara, Tomoki (2021). Enabling energy system transition toward decarbonization in Japan through energy service demand reduction. Energy 227, e120464. 10.1016/j.energy.2021.120464.

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 777, e146200. 10.1016/j.scitotenv.2021.146200.

Morais, T.G., Teixeira, R.F.M., Lauk, C., Theurl, M.C., Winiwarter, W. , Mayer, A., Kaufmann, L., Haberl, H., et al. (2021). Agroecological measures and circular economy strategies to ensure sufficient nitrogen for sustainable farming. Global Environmental Change 69, e102313. 10.1016/j.gloenvcha.2021.102313.

Yue, H, Worrell, E, Crijns-Graus, W, & Zhang, S. (2021). The potential of industrial electricity savings to reduce air pollution from coal-fired power generation in China. Journal of Cleaner Production 301, e126978. 10.1016/j.jclepro.2021.126978.

Benveniste, H. , Crespo Cuaresma, J., Gidden, M. , & Muttarak, R. (2021). Tracing international migration in projections of income and inequality across the Shared Socioeconomic Pathways. Climatic Change 166 (3-4) 10.1007/s10584-021-03133-w.

Brutschin, E., Pianta, S., Tavoni, M., Riahi, K. , Bosetti, V., Marangoni, G., & van Ruijven, B.J. (2021). A multidimensional feasibility evaluation of low-carbon scenarios. Environmental Research Letters 16 (6), 064069. 10.1088/1748-9326/abf0ce.

Böttcher, K., Paunu, V.-V., Kupiainen, K., Zhizhin, M., Matveev, A., Savolahti, M., Klimont, Z. , Väätäinen, S., et al. (2021). Black carbon emissions from flaring in Russia in the period 2012-2017. Atmospheric Environment 254, e118390. 10.1016/j.atmosenv.2021.118390.

Parkinson, S. (2021). Guiding urban water management towards 1.5 ℃. npj Clean Water 10.1038/s41545-021-00126-1. (In Press)

Pianta, S., Brutschin, E., van Ruijven, B. , & Bosetti, V. (2021). Faster or slower decarbonization? Policymaker and stakeholder expectations on the effect of the COVID-19 pandemic on the global energy transition. Energy Research & Social Science 76, e102025. 10.1016/j.erss.2021.102025.

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