Patrícia Fortes
Universidade Nova de Lisboa
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Climate Policy | 2013
Patrícia Fortes; Sofia Simoes; Júlia Seixas; Denise Van Regemorter; Francisco Ferreira
Bottom-up and top-down models are used to support climate policies, to identify the options required to meet GHG abatement targets and to evaluate their economic impact. Some studies have shown that the GHG mitigation options provided by economic top-down and technological bottom-up models tend to vary. One reason for this is that these models tend to use different baseline scenarios. The bottom-up TIMES_PT and the top-down computable general equilibrium GEM-E3_PT models are examined using a common baseline scenario to calibrate them, and the extend of their different mitigation options and its relevant to domestic policy making are assessed. Three low-carbon scenarios for Portugal until 2050 are generated, each with different GHG reduction targets. Both models suggest close mitigation options and locate the largest mitigation potential to energy supply. However, the models suggest different mitigation options for the end-use sectors: GEM-E3_PT focuses more on energy efficiency, while TIMES_PT relies on decrease carbon intensity due to a shift to electricity. Although a common baseline scenario cannot be ignored, the models’ inherent characteristics are the main factor for the different outcomes, thereby highlighting different mitigation options. Policy relevance The relevance of modelling tools used to support the design of domestic climate policies is assessed by evaluating the mitigation options suggested by a bottom-up and a top-down model. The different outcomes of each model are significant for climate policy design since each suggest different mitigation options like end-use energy efficiency and the promotion of low-carbon technologies. Policy makers should carefully select the modelling tool used to support their policies. The specific modelling structures of each model make them more appropriate to address certain policy questions than others. Using both modelling approaches for policy support can therefore bring added value and result in more robust climate policy design. Although the results are specific for Portugal, the insights provided by the analysis of both models can be extended to, and used in the climate policy decisions of, other countries.
Archive | 2015
Alessandro Chiodi; Peter G. Taylor; Júlia Seixas; Sofia Simoes; Patrícia Fortes; João Pedro Gouveia; Luís Dias; Brian P. Ó Gallachóir
A key objective of IEA-ETSAP is to assist decision makers in robustly developing, implementing and assessing the impact of energy and climate mitigation policies. This chapter focuses on four case studies, in which there is clear evidence of a direct link between the use of MARKAL and TIMES scenario modelling activities and the resulting policy decisions. The case studies selected assess how the (i) UK MARKAL model informed the development of energy and climate mitigation policy in the UK, focusing on the Energy White Paper in 2003, the Energy White Paper in 2007 and the Climate Change Act in 2008; (ii) Irish TIMES model informed the development of climate mitigation legislation in Ireland in 2014 and Ireland’s negotiating position regarding the EU 2030 Climate Energy Package in 2014; (iii) TIMES_PT model informed climate policy in Portugal in the last 10 years and has supported the design of climate mitigation policies; (iv) IEA ETP Model informed the G8 in responding to the 2005 Gleneagles Plan of Action and has supported the work of the Major Economies Forum and Clean Energy Ministerial. This chapter collates methodologies and results from these different case studies and summarizes some key findings regarding (i) policy frameworks and goals; (ii) how policy makers have been intertwined with the modelling tool during the modelling process; (iii) the role of the economic stakeholders dialogue; (iv) main insights from the modelling exercises; (v) lessons learnt: from effective contributions to real limitations and (vi) recommendations.
Technological Forecasting and Social Change | 2015
Patrícia Fortes; António Alvarenga; Júlia Seixas; Sofia Rodrigues
Energy | 2014
Patrícia Fortes; Rui M. Pereira; Alfredo M. Pereira; Júlia Seixas
Energy Policy | 2015
Júlia Seixas; Sofia Simoes; Luís Dias; Amit Kanudia; Patrícia Fortes; Maurizio Gargiulo
Renewable & Sustainable Energy Reviews | 2017
Carla Teotónio; Patrícia Fortes; Peter Roebeling; Miguel Rodríguez; Margarita Robaina-Alves
Technological Forecasting and Social Change | 2015
Sofia Simoes; Patrícia Fortes; Júlia Seixas; Gjalt Huppes
Energy Efficiency | 2014
Sofia Simoes; Júlia Seixas; Patrícia Fortes; Gjalt Huppes
Informing Energy and Climate Policies Using Energy Systems Models | 2015
James Glynn; Patrícia Fortes; Anna Krook-Riekkola; Maryse Labriet; Marc Vielle; Socrates Kypreos; Antti Lehtilä; Peggy Mischke; Hancheng Dai; Maurizio Gargiulo; Per Ivar Helgesen; Tom Kober; Phil Summerton; Bruno Merven; Sandrine Selosse; Kenneth Bernard Karlsson; Neil Strachan; Brian P. Ó Gallachóir
Energy Procedia | 2013
Amit Kanudia; Niels Berghout; Dulce Boavida; Machteld van den Broek; Helena Cabal; Júlio F. Carneiro; Patrícia Fortes; Maurizio Gargiulo; João Pedro Gouveia; Maryse Labriet; Yolanda Lechón; Roberto Martinez; Paulo Mesquita; Abdelkrim Rimi; Júlia Seixas; GianCarlo Tosato