Top-down and bottom-up modelling to support low-carbon scenarios: climate policy implications

Fortes, Patrícia; Simões, Sofia; Seixas, Júlia; Regemorter, Denise Van; Ferreira, Francisco

doi:10.1080/14693062.2013.768919

Cited by 35 publications

(25 citation statements)

References 21 publications

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“…The reason is that potential extremes, possibly arising from policy conditions' imposition, would be limited by the coupling constraints. The relevance of such an integration to reflect climate policy has also been highlighted in Fortes et al (2013).…”

Section: Pertinence Of the Methodologymentioning

confidence: 99%

Combination of equilibrium models and hybrid life cycle - input–output analysis to predict the environmental impacts of energy policy scenarios

et al. 2015

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Nowadays, many countries adopt an active agenda to mitigate the impact of greenhouse gas emissions by moving towards less polluting energy generation technologies. The environmental costs, directly or indirectly generated to achieve such a challenging objective, remain however largely underexplored. Until now, research has focused either on pure economic approaches such as computable general equilibrium (CGE) and partial equilibrium (PE) models, or on (physical) energy supply scenarios. These latter could be used to evaluate the environmental impacts of various energy saving or cleaner technologies via life cycle assessment (LCA) methodology. These modelling efforts have, however, been pursued in isolation, without exploring the possible complementarities and synergies. In this study, we have undertaken a practical combination of these approaches into a common framework: on the one hand, by coupling a CGE with a PE model, and, on the other hand, by linking the outcomes from the coupling with a hybrid inputoutput−process based life cycle inventory. The methodological framework aimed at assessing the environmental consequences of two energy policy scenarios in Luxembourg between 2010 and 2025. The study highlights the potential of coupling CGE and PE models but also the related methodological difficulties (e.g. small number of available technologies in Luxembourg, intrinsic limitations of the two approaches, etc.). The assessment shows both environmental synergies and trade-offs due to the implementation of energy policies. For example, despite the changes in technologies towards the reduction of greenhouse gas emissions, only marginal improvements are observed in the climate change mitigation scenario as compared to the business-as-usual. The energy related production and imports are indeed expected to increase over time and represent a large contribution to the country's impacts. Interestingly, side effects on other impacts than climate change or fossil resource depletion (e.g. ionising radiation and water depletion) may also occur mainly due to the use of nuclear energy in neighbouring countries.

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Section: Pertinence Of the Methodologymentioning

confidence: 99%

Combination of equilibrium models and hybrid life cycle - input–output analysis to predict the environmental impacts of energy policy scenarios

et al. 2015

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“…Fortes et al (2013) have adopted a similar approach to couple GEM-E3-Portugal and TIMES-Portugal, inspired by preliminary version of this work. They applied this coupling framework only to the reference case.…”

Section: The Coupling Methodologymentioning

confidence: 99%

Assessment of the Effectiveness of Global Climate Policies Using Coupled Bottom-Up and Top-Down Models

et al. 2015

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(150 words)In order to assess climate mitigation agreements, we propose an iterative procedure linking TIAM-WORLD, a global technology-rich optimization model, and GEMINI-E3, a global general equilibrium model. The coupling methodology combines the precise representation of energy and technology choices with a coherent representation of the macro-economic impacts, especially in terms of trade effects of climate policies on energy-intensive products. In climate mitigation scenarios, drastic technology breakthroughs are required as soon as possible, especially in large emitting countries, and in all sectors of the economy. Energy-intensive industries tend to be delocalized in regions where low-carbon production is feasible and cheap, or in regions without emission cap. However, emission leakage remains small, mainly due to global lower oil demand, and energy exporting countries are extremely penalized given lower energy exports. Emission reduction at least in the power sector and in energy-intensive industries of developing countries must be considered to reach the 2°C target.

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“…Although the authors give some pedagogic examples of their approach, such generalized formulations linking top-down with bottom-up models are not yet developed. Nevertheless, quite a few efforts are undertaken to integrate, based on soft linking methods, TIMES with general equilibrium models like, e.g., GEMINI-E3 [8], GEM-E3 [9], in order to capture sectoral impacts in terms of welfare and labor losses as function of stringent environmental policies 1 .…”

Section: Introductionmentioning

confidence: 99%

Decomposing TIAM-MACRO to Assess Climatic Change Mitigation

Kypreos

Lehtilä

2015

Environ Model Assess

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TIAM-MACRO (TM) is a mathematical programming growth model where the global multi-region bottom-up engineering model TIAM is linked with a topdown macroeconomic module MACRO to maximize an inter-temporal utility function for a single representative producer-consumer agent in each region. The size of TM is such that non-linear (NL) optimal solutions cannot be obtained even when the best available personal computers and solvers are used. Therefore, an alternative is proposed based on decomposition methods converting TM to a small-size NL macroeconomic model, called TIAM-MACRO Stand-Alone (TMSA), and where the energy model TIAM is substituted by appropriate quadratic costsupply functions (QSF). The TIAM model and the TMSA are calibrated to the demands estimated with a scenario generator and are then solved iteratively. This report concentrates on the description and foundation of the algorithm and explains why an adjusted production function is needed to allow for sectoral income and price elasticities that reproduce/calibrate the baseline scenario. It is shown that the decomposed problem for a single region is calibrated and solved to exactly the same results as the original problem in 3 min of computer time instead of 2-3 h without decomposition. Also, for the first time, we are able to solve the global TM model with 15 regions in 1.5 h applying the approach based on TMSA (in Windows 7, 64-bit workstation, solution in a single thread).

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Top-down and bottom-up modelling to support low-carbon scenarios: climate policy implications

Cited by 35 publications

References 21 publications

Combination of equilibrium models and hybrid life cycle - input–output analysis to predict the environmental impacts of energy policy scenarios

Combination of equilibrium models and hybrid life cycle - input–output analysis to predict the environmental impacts of energy policy scenarios

Assessment of the Effectiveness of Global Climate Policies Using Coupled Bottom-Up and Top-Down Models

Decomposing TIAM-MACRO to Assess Climatic Change Mitigation

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