67 research outputs found

    Exploring the use of dynamic linear panel data models for evaluating energy/economy/environment models — an application for the transportation sector

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    This paper uses the RoSE transportation sector scenarios of the GCAM and REMIND energy-economy-models for the U.S. region to derive and compare these models’ intrinsic elasticities with those resulting from historical trends, estimates from the literature, and across each other. To estimate the model-intrinsic elasticities, we explore the use of dynamic linear panel data models. On the basis of 26 scenarios (panels) between 2010 and 2050, our analysis suggests that nearly all model-intrinsic elasticities with respect to final energy use are roughly comparable to each other, to those observed historically, and to those from other studies. The key difference is these models’ comparatively low intrinsic income elasticity of final energy use. This and other minor differences are interpreted through key assumptions underlying both energy-economy-models

    Narrative-driven alternative roads to achieve mid-century CO2 net neutrality in Europe

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    The tightened climate mitigation targets of the EU green deal raise an important question: Which strategy should be used to achieve carbon emissions net neutrality? This study explores stakeholder-designed narratives of the future energy system development within the deep decarbonization context. European carbon net-neutrality goals are put under test in a model comparison exercise using state of the art Energy-Environment-Economy (E3) models: ETM-UCL, PRIMES and REMIND. Results show that while achieving the transition to carbon neutrality by mid-century is feasible under quite different future energy systems, some robust commonalities emerge. Electrification of end use sectors combined with large-scale expansion of renewable energy is a no-regret decision for all strategies; Carbon Dioxide Removal (CDR) plays an important role for achieving net-neutral targets under all scenarios, but is most relevant when demand-side changes are limited; hydrogen and synthetic fuels can be a relevant mitigation option for mid-century mitigation in hard-to-abate sectors; energy efficiency can reduce the supply system strain. Finally, high carbon prices (300-900€/tCO2) are needed under all strategies in order to achieve carbon net neutrality in 2050

    Fossil extraction bans and carbon taxes: Assessing their interplay through multiple models

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    Given concerns about the ambition and effectiveness of current climate policies, a case has been made for the combination of demand side policies such as carbon pricing with supply side bans on fossil fuel extraction. However, little is known about their interplay in the context of climate stabilization strategies. Here, we present a multi-model assessment quantifying the effectiveness of supply side policies and their interactions with demand-side ones. We explore a variety of fossil fuel bans with four integrated assessment models and find that international supply side policies reduce carbon emissions but not at sufficient levels to stabilize temperature increase to well below 2°C. When combined with demand side policies, supply side policies reduce the required carbon price, dampen reliance on CO2 removal technologies, and increase investment in renewable energy. The results indicate the opportunity to integrate fossil fuel bans alongside price-based policies when exploring pathways to reach ambitious mitigation targets

    Energy Investments under Climate Policy: A Comparison of Global Models

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    The levels of investment needed to mobilize an energy system transformation and mitigate climate change are not known with certainty. This paper aims to inform the ongoing dialogue and in so doing to guide public policy and strategic corporate decision making. Within the framework of the LIMITS integrated assessment model comparison exercise, we analyze a multi-IAM ensemble of long-term energy and greenhouse gas emissions scenarios. Our study provides insight into several critical but uncertain areas related to the future investment environment, for example in terms of where capital expenditures may need to flow regionally, into which sectors they might be concentrated, and what policies could be helpful in spurring these financial resources. We find that stringent climate policies consistent with a 2 degrees C climate change target would require a considerable upscaling of investments into low-carbon energy and energy efficiency, reaching approximately 45trillion(range:45 trillion (range: 30-75 trillion) cumulative between 2010 and 2050, or about 1.1trillionannually.Thisrepresentsanincreaseofsome1.1 trillion annually. This represents an increase of some 30 trillion (10−55trillion),or10-55 trillion), or 0.8 trillion per year, beyond what investments might otherwise be in a reference scenario that assumes the continuation of present and planned emissions-reducing policies throughout the world. In other words, a substantial "clean-energy investment gap" of some 800billion/yrexists−−notablyonthesameorderofmagnitudeaspresent−daysubsidiesforfossilenergyandelectricityworldwide(800 billion/yr exists -- notably on the same order of magnitude as present-day subsidies for fossil energy and electricity worldwide (523 billion). Unless the gap is filled rather quickly, the 2 degrees C target could potentially become out of reach

    Religion and Self: Notions from a Cultural Psychological Perspective

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    After a brief introduction of a cultural psychological perspective, this paper turns to the concept of self. The paper proposes to conceive of that reality to which the concepts of self refer as a narrative, employing especially autobiographies and other ego-documents in empirical exploration. After discussing some psychological theories about “self,” the paper points out that they may well be applied in research on personal religiosity

    A low energy demand scenario for meeting the 1.5 °C target and sustainable development goals without negative emission technologies

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    Scenarios that limit global warming to 1.5 °C describe major transformations in energy supply and ever-rising energy demand. Here, we provide a contrasting perspective by developing a narrative of future change based on observable trends that results in low energy demand. We describe and quantify changes in activity levels and energy intensity in the global North and global South for all major energy services. We project that global final energy demand by 2050 reduces to 245 EJ, around 40% lower than today, despite rises in population, income and activity. Using an integrated assessment modelling framework, we show how changes in the quantity and type of energy services drive structural change in intermediate and upstream supply sectors (energy and land use). Down-sizing the global energy system dramatically improves the feasibility of a low-carbon supply-side transformation. Our scenario meets the 1.5 °C climate target as well as many sustainable development goals, without relying on negative emission technologies

    Comparing energy system optimization models and integrated assessment models: Relevance for energy policy advice

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    Background: The transition to a climate neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system optimisation models (ESOMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESOMs have rarely been compared or linked with one another. Methods: This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables. We define harmonised regions and a subset of shared result variables that enable the comparison of scenario results across the models. Results: The results highlight how power generation and demand development are related and driven by regional and sectoral drivers. They also show that demand developments like for hydrogen can be linked with power generation potentials such as onshore wind power. Lastly, the results show that the role of nuclear power is related to the availability of wind resources. Conclusions: This comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESOM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind. The comparison shows that regional aggregations might conceal differences within regions that are potentially of interest for national policy makers thereby indicating a need for national-level analysis

    Identifying energy model fingerprints in mitigation scenarios

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    Energy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies
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