Decarbonisation pathways for local authorities, citizen and businesses

External resources

Within its activities, LOCALISED collects and makes available interesting information from some external sources which identified as interesting, without pretending to be exhaustive.

With this we intend to flank transformative challenges for cities and regions in regard to decarbonisation

Energy and emission downscaling

Costa, L., Moreau, V., Thurm, B., Yu, W., Clora, F., Baudry, G., Warmuth, H., Hezel, B., Seydewitz, T., Ranković, A., Kelly, G., Kropp, J. P. (2021). The decarbonisation of Europe powered by lifestyle changes. Environmental Research Letters, 16(4), 044057.

Clora, F., Yu, W., Baudry, G., & Costa, L. (2021). Impacts of supply-side climate change mitigation practices and trade policy regimes under dietary transition: the case of European agriculture. Environmental Research Letters, 16(12), 124048.

Development and modelling of different decarbonization scenarios of the European energy system until 2050 as a contribution to achieving the ambitious 1.5 ◦C climate target – establishment of open source/data modelling in the European H2020 project openENTRANCE.

Moran, D., Pichler, P. P., Zheng, H., Muri, H., Klenner, J., Kramel, D., … & Gurney, K. R. (2022). Estimating CO 2 emissions for 108 000 European cities. Earth System Science Data, 14(2), 845-864.

Pan-European Thermal Atlas 4.3An interactive tool that allows for the download of a variety of data useful for heat planning.

Verstraete, J. (2016). The spatial disaggregation problem: simulating reasoning using a fuzzy inference systemIEEE Transactions on Fuzzy Systems, 25(3), 627-641.

Monteiro, J., Martins, B., & Pires, J. M. (2018). A hybrid approach for the spatial disaggregation of socio-economic indicatorsInternational Journal of Data Science and Analytics, 5(2), 189-211.

Regional Business Vulnerability to Decarbonisation

Wang, S., & Chen, B. (2018). Three-Tier carbon accounting model for citiesApplied Energy, 229, 163-175. 

Fiedler, T., Pitman, A. J., Mackenzie, K., Wood, N., Jakob, C., & Perkins-Kirkpatrick, S. E. (2021). Business risk and the emergence of climate analyticsNature Climate Change, 11(2), 87-94.

Pankratz, N., & Schiller, C. (2021, June). Climate change and adaptation in global supply-chain networks. In Proceedings of Paris December 2019 Finance Meeting EUROFIDAI-ESSEC, European Corporate Governance Institute–Finance Working Paper (No. 775).

Lo, A. Y., Liu, S., Chow, A. S., Pei, Q., Cheung, L. T., & Fok, L. (2021). Business vulnerability assessment: a firm-level analysis of micro-and small businesses in China. Natural Hazards, 108(1), 867-890

Synergies between mitigation and adaptation

Selection tool and database about climate change-related adaptation strategies at local level developed by the RESCCUE project.

openTEPES model (Open Generation and Transmission Operation and Expansion Planning Model). A model that analyses the impact of the implementation of specific energy policies on the development of the power transmission network.

Climate-ADAPT. Database of European Adaptation & Mitigation Measures, Case Studies, and Indicators.

Urban Adaptation e-Guide of the RESIN project. Support platform for knowledge, support and tools to develop an urban climate adaptation plan.

Adaptation Options Library of the RESIN project. Data tool allowing spatial and sectoral filtering of adaptation measures developed as a part of the RESIN project. Presents synergies and tradeoffs when available.

Duguma, L. A., Minang, P. A., & van Noordwijk, M. (2014). Climate change mitigation and adaptation in the land use sector: from complementarity to synergyEnvironmental management, 54(3), 420-432. 

Peñasco, C., Anadón, L. D., & Verdolini, E. (2021). Systematic review of the outcomes and trade-offs of ten types of decarbonization policy instrumentsNature Climate Change, 11(3), 257-265.

Making sustainable decarbonization plans of cities operational management tools

Fekete, H., Kuramochi, T., Roelfsema, M., den Elzen, M., Forsell, N., Höhne, N., … & Gusti, M. (2021). A review of successful climate change mitigation policies in major emitting economies and the potential of global replicationRenewable and Sustainable Energy Reviews, 137, 110602.


EUCalc model – The EUCalc models energy, resources, production and food systems at the EU level + UK and Switzerland (EU27+2) under pre-defined (but adjustable) levels of ambitions in regard to technological deployment and consumption behaviour. The modelling approach was inspired by the family of so called 2050 Calculators which were spearheaded by the call for more transparent approaches to address the challenge of reducing carbon emissions. You find the EUCalc model and source code at this.

Python Libraries:

  • The open-source Python package pyam provides a suite of tools and functions for analysing and visualising input data (i.e., assumptions/parametrization) and results (model output) of integrated-assessment models, macro-energy scenarios, energy systems analysis, and sectoral studies.
  • PyPSA-Eur-Sec builds on the electricity generation and transmission model PyPSA-Eur to add demand and supply for the following sectors: transport, space and water heating, biomass, industry and industrial feedstocks, agriculture, forestry and fishing. This completes the energy system and includes all greenhouse gas emitters except waste management and land use.
  • DEAP is an evolutionary algorithm framework in python allowing rapid scaling of evolutionary algorithm analyses and allowing for parallelisation and multi-objective analysis types.

Gams Model – GENeSYS-MOD v3.0 [Global Energy System Model] with additional equations for ramping, ramping costs, and minimal runtime requirements. Test dataset for Middle-earth included. GENeSYS-MOD is a linear program, minimizing total system costs. Energy demands are exogenously predefined and the model needs to provide the necessary capacities to meet them. To achieve a cost-optimal energy mix, the model considers a plethora of different technology options, including generation, sector coupling, and storages.

Jacobson, M. Z., von Krauland, A. K., Coughlin, S. J., Palmer, F. C., & Smith, M. M. (2022). Zero air pollution and zero carbon from all energy at low cost and without blackouts in variable weather throughout the US with 100% wind-water-solar and storageRenewable Energy, 184, 430-442.

Nagy, Z., Felkner, J., Beck, A. L., Reeves, D. C., Richter, S., Shastry, V., … & Rai, V. (2022). IMPACT: Integrated Multi-Domain Emission Pathways For Cities Under Land-Use Policy, Technology Adoption, Climate Change And Grid DecarbonizationarXiv preprint arXiv:2202.07458.

Auer, H., Crespo del Granado, P., Oei, P. Y., Hainsch, K., Löffler, K., Burandt, T., … & Grabaak, I. (2020). Development and modelling of different decarbonization scenarios of the European energy system until 2050 as a contribution to achieving the ambitious 1.5∘ C climate target – establishment of open source/data modelling in the European H2020 project openENTRANCEe & i Elektrotechnik und Informationstechnik, 137(7), 346-358.

Victoria, M., Zhu, K., Brown, T., Andresen, G. B., & Greiner, M. (2020). Early decarbonisation of the European energy system pays off. Nature communications, 11(1), 1-9.

Muñoz, D. S., & García, J. L. D. (2021). GIS-based tool development for flooding impact assessment on electrical sector. Journal of Cleaner Production, 320, 128793.

Sánchez-Muñoz, D., Domínguez-García, J. L., Martínez-Gomariz, E., Russo, B., Stevens, J., & Pardo, M. (2020). Electrical grid risk assessment against flooding in Barcelona and Bristol cities. Sustainability, 12(4), 1527.

ENERMAPS project