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Energy scenarios describing transition pathways towards low-emission energy systems are commonly used to design mitigation strategies. There is a growing awareness in the research community that energy transitions should be understood as socio-technical transitions and that energy scenario construction should reflect this fact. This paper presents an application of a socio-technical scenario building method for improving long-term scenarios and strategies for the energy transition in Germany. Developing integrated scenarios on a national level starts with employing the cross impact balancing (CIB) approach for identifying consistent societal scenarios. As a first step, relevant context factors are selected and defined (39 descriptors and alternative future developments). Interviews with experts are used to develop a qualitative impact network for the CIB. The resulting context scenarios are then transferred to quantitative energy scenarios by using two different energy models that account for energy demand and supply structures for Germany. A final evaluation focuses on primary energy demand, renewable energy shares, and direct energy-related CO2 emissions. The approach integrates statements of societal and energy model experts and results in an interdisciplinary knowledge integration. This in turn provides insight into the method’s capacity to improve the consistency of energy scenarios and to identify potential societal risks related to the energy transition process.

PurposeThe concept of criticality concerns the probability and the possible impacts of shortages in raw-material supply and is usually applied to regional economies or specific industries. With more and more products being highly dependent on potentially critical raw materials, efforts are being made to also incorporate criticality into the framework of life cycle sustainability assessment (LCSA). However, there is still some need for methodological development of indicators to measure raw-material criticality in LCSA.MethodsWe therefore introduce ‘economic product importance’ (EPI) as a novel parameter for the product-specific evaluation of the relevance and significance of a certain raw material for a particular product system. We thereby consider both the actual raw-material flows (life cycle inventories) and the life cycle cost. The EPI thus represents a measure for the material-specific product-system vulnerability (another component being the substitutability). Combining the product-system vulnerability of a specific product system towards a certain raw material with the supply disruption probability of that same raw material then yields the product-system specific overall criticality with regard to that raw material. In order to demonstrate our novel approach, we apply it to a case study on a battery-electric vehicle.ResultsSince our approach accounts for the actual amounts of raw materials used in a product and relates their total share of costs to the overall costs of the product, no under- or over-estimation of the mere presence of the raw materials with respect to their relevance for the product system occurs. Consequently, raw materials, e.g. rare earth elements, which are regularly rated highly critical, do not necessarily reach higher criticality ranks within our approach, if they are either needed in very small amounts only or if their share in total costs of the respective product system is very low. Accordingly, in our case study on a battery-electric vehicle product system, most rare earth elements are ranked less critical than bulk materials such as copper or aluminium.ConclusionOur EPI approach constitutes a step forward towards a methodology for the raw-material criticality assessment within the LCSA framework, mainly because it allows a product-specific evaluation of product-system vulnerability. Furthermore, it is compatible with common methods for the supply disruption probability calculation — such as GeoPolRisk, ESP or ESSENZ — as well as with available substitutability evaluations. The practicability and usefulness of our approach has been shown by applying it to a battery-electric vehicle.

Newly industrialized countries face major challenges to comply with the Paris Treaty targets as economic growth and prosperity lead to increasing energy demand. Our paper analyses technological and structural options in terms of energy efficiency and renewable energies for a massive reduction of energy-related CO2 emissions in Latin America. Brazil and Mexico share similar growth prospects but differ significantly with respect to renewable energy potentials. We identify, how this leads to different transformation pathways. By applying an energy system balancing model we develop normative energy system transformation scenarios across the heating, power, and mobility sectors, including their potential interactions. The normative scenarios rely on three basic strategies for both countries: (1) strong exploitation of efficiency potentials; (2) tapping the renewable energy potentials; and (3) sector coupling and electrification of heat supply and transport. Despite economic growth, significant CO2 emission reductions could be achieved in Brazil from 440 Gt/a (2.2 t/cap) in 2012 to 0.4 Gt (2 kg/cap) in 2050 and in Mexico from 400 Gt/a (3.3 t/cap) to 80 Gt (0.5 t/cap). Our study shows the gap between existing policy and scenarios and our strategies, which provide an economically feasible way to comply with the Paris treaty targets.

It is still possible to comply with the Paris Climate Agreement to maintain a global temperature ‘well below +2.0 °C’ above pre-industrial levels. We present two global non-overshoot pathways (+2.0 °C and +1.5 °C) with regional decarbonization targets for the four primary energy sectors—power, heating, transportation, and industry—in 5-year steps to 2050. We use normative scenarios to illustrate the effects of efficiency measures and renewable energy use, describe the roles of increased electrification of the final energy demand and synthetic fuels, and quantify the resulting electricity load increases for 72 sub-regions. Non-energy scenarios include a phase-out of net emissions from agriculture, forestry, and other land uses, reductions in non-carbon greenhouse gases, and land restoration to scale up atmospheric CO2 removal, estimated at −377 Gt CO2 to 2100. An estimate of the COVID-19 effects on the global energy demand is included and a sensitivity analysis describes the impacts if implementation is delayed by 5, 7, or 10 years, which would significantly reduce the likelihood of achieving the 1.5 °C goal. The analysis applies a model network consisting of energy system, power system, transport, land-use, and climate models.

We integrate life cycle indicators for various technologies of an energy system model with high spatiotemporal detail and a focus on Europe and North Africa. Using multi-objective optimization, we calculate a pareto front that allows us to assess the trade-offs between system costs and life cycle greenhouse gas (GHG) emissions of future power systems. Furthermore, we perform environmental ex-post assessments of selected solutions using a broad set of life cycle impact categories. In a system with the least life cycle GHG emissions, the costs would increase by ~63%, thereby reducing life cycle GHG emissions by ~82% compared to the cost-optimal solution. Power systems mitigating a substantial part of life cycle GHG emissions with small increases in system costs show a trend towards a deployment of wind onshore, electricity grid and a decline in photovoltaic plants and Li-ion storage. Further reductions are achieved by the deployment of concentrated solar power, wind offshore and nuclear power but lead to considerably higher costs compared to the cost-optimal solution. Power systems that mitigate life cycle GHG emissions also perform better for most impact categories but have higher ionizing radiation, water use and increased fossil fuel demand driven by nuclear power. This study shows that it is crucial to consider upstream GHG emissions in future assessments, as they represent an inheritable part of total emissions in ambitious energy scenarios that, so far, mainly aim to reduce direct CO2 emissions.

Background Linking qualitative scenarios with quantitative models is a common approach to integrate assumptions on possible future societal contexts into modeling. But reflection on how and to what degree knowledge is effectively integrated during this endeavor does not generally take place. In this paper, we reflect on the performance of a specific hybrid scenario approach (qualitative Cross-Impact Balance analysis, CIB, linked with quantitative energy models) concerning knowledge integration through 11 different process steps. In order to guide the scenario community in applying this approach, we reflect on general methodological features as well as different design options. We conceptualize different forms of interdisciplinary knowledge integration (compiling, combining and synthesizing) and analyze how and to what degree knowledge about society and uncertainty are integrated into scenario process and products. In addition, we discuss trade-offs regarding design choices and forms of knowledge integration. Results On the basis of three case studies, we identify two general designs of linking which build on each other (basic and extended design) and which differ in essence regarding the balance of power between the CIB and the energy modeling. Ex post assessment of the form of interdisciplinary knowledge integration in each step revealed that specific method properties of CIB as well as the interaction with additional quantitative as well as specific qualitative methods foster distinct forms of knowledge integration. The specific roles assigned to CIB in the hybrid scenario process can also influence the form of knowledge integration. Conclusions In this study, we use a joint process scheme linking qualitative context scenarios with energy modeling. By applying our conceptualization of different forms of knowledge integration we analyze the designs’ respective potential for and respective effects on knowledge integration. Consequently, our findings can give guidance to those who are designing their own hybrid scenario processes. As this is an explorative study, it would be useful to further test our hypotheses in different hybrid scenario designs. Finally, we note that at some points in the process a more precise differentiation of three forms of knowledge integration would have been useful and propose to further differentiate and detail them in future research.

Background Given the multitude of scenarios on the future of our energy systems, multi-criteria assessments are increasingly called for to analyze and assess desired and undesired effects of possible pathways with regard to their environmental, economic and social sustainability. Existing studies apply elaborate lists of sustainability indicators, yet these indicators are defined and selected by experts and the relative importance of each indicator for the overall sustainability assessments is either determined by experts or is computed using mathematical functions. Target group-specific empirical data regarding citizens’ preferences for sustainability indicators as well as their reasoning behind their choices are not included in existing assessments. Approach and results We argue that citizens’ preferences and values need to be more systematically analyzed. Next to valid and reliable data regarding diverse sets of indicators, reflections and deliberations are needed regarding what different societal actors, including citizens, consider as justified and legitimate interventions in nature and society, and what considerations they include in their own assessments. For this purpose, we present results from a discrete choice experiment. The method originated in marketing and is currently becoming a popular means to systematically analyze individuals’ preference structures for energy technology assessments. As we show in our paper, it can be fruitfully applied to study citizens’ values and weightings with regard to sustainability issues. Additionally, we present findings from six focus groups that unveil the reasons behind citizens’ preferences and choices. Conclusions Our combined empirical methods provide main insights with strong implications for the future development and assessment of energy pathways: while environmental and climate-related effects significantly influenced citizens’ preferences for or against certain energy pathways, total systems and production costs were of far less importance to citizens than the public discourse suggests. Many scenario studies seek to optimize pathways according to total systems costs. In contrast, our findings show that the role of fairness and distributional justice in transition processes featured as a dominant theme for citizens. This adds central dimensions for future multi-criteria assessments that, so far, have been neglected by current energy systems models.

Energy scenarios represent a prominent tool to support energy system transitions towards sustainability. In order to better fulfil this role, two elements are widely missing in previous work on designing, analyzing, and using scenarios: First, a more systematic integration of social and socio-technical characteristics of energy systems in scenario design, and, second, a method to apply an accordingly enhanced set of indicators in scenario assessment. In this article, an integrative scenario assessment methodology is introduced that combines these two requirements. It consists of: (i) A model-based scenario analysis using techno-economic and ecological indicators; (ii) a non-model-based analysis using socio-technical indicators; (iii) an assessment of scenario performances with respect to pre-determined indicator targets; (iv) a normalization method to make the two types of results (model-based and non-model-based) comparable; (v) an approach to classify results to facilitate structured interpretation. The combination of these elements represents the added-value of this methodology. It is illustrated for selected indicators, and exemplary results are presented. Methodological challenges and remaining questions, e.g., regarding the analysis of non-model-based indicators, resource requirements, or the robustness of the methodology are pointed out and discussed. We consider this integrative methodology being a substantial improvement of previous scenario assessment methodologies.

Background Different strategies have been proposed for transforming the energy system in Germany. To evaluate their sustainability, it is necessary to analyze their macroeconomic and distributional effects. An approach to do this analysis in an integrated consistent framework is presented here. Methods Comparing ten energy transition scenarios with emission reduction targets by 2050 of 80% or 95%, respectively, allows evaluating a broad range of energy system transformation strategies with respect to the future technology and energy carrier mix. For this purpose, an energy system model and a macroeconometric model are combined, thus re-modeling the unified scenarios. An important extension of the model was concerned with the integration of synthetic fuels into the energy-economy model. One focus besides the overall macroeconomic assessment is the regional analysis. For this purpose, own assumptions on the regional distribution of the expansion of renewable energies were developed. Results The effects on gross domestic product (GDP) and employment are similar on average from 2030 to 2050 across the scenarios, with most of the more ambitious scenarios showing slightly higher values for the socioeconomic variables. Employment in the construction sector shows the largest effects in most scenarios, while in the energy sector employment is lower in scenarios with high energy imports. At the regional level, the differences between scenarios are larger than at the national level. There is no clear or stable regional pattern of relative loss and profit from the very ambitious transformation, as not only renewable energy expansion varies, and hydrogen strategies enter the scene approaching 2050. Conclusions From the relatively small differences between the scenarios, it can be concluded that, from a macroeconomic perspective, it is not decisive for the overall economy which (supply side) strategy is chosen for the transformation of the energy system. More effort needs to be put into improving assumptions and modeling approaches related to strategies for achieving the final 20% CO 2 reduction, for example the increasing use of hydrogen.

Estimates of the global biospheric excess 14C inventory IB14,E from Naegler and Levin (2009) were used to constrain the age distribution a(τ) in heterotrophically respired CO2 with a simple (radio)carbon model of the global biosphere. Subsequently, a(τ) could be used to estimate the global gross carbon exchange FeqC (net primary productivity, NPP, and heterotrophic respiration) between atmosphere and biosphere as well as both the δ13C and Δ14C signatures in heterotrophically respired CO2 (δ13CRH and Δ14CRH, respectively). Our estimates of FeqC range from 41 to 64 petagrams carbon per year (Pg C a−1), with a best estimate of 55 Pg C a−1. The uncertainty of this value is dominated by the uncertainties of IB14,E and of the net biospheric uptake of anthropogenic CO2. Limitations intrinsic to our approach as well as uncertainties in effective global average atmospheric Δ14CO2 add an uncertainty of ±3 Pg C a−1. The δ13CRH of heterotrophically respired CO2 lags the δ13C of assimilated CO2 by ∼10–17 years. This leads to a somewhat smaller estimate of the biospheric 13CO2 disequilibrium flux than previously assumed. Δ14CRH increased from ∼−20‰ in the early 1950s to maximum values of 300–325‰ in the late 1960s/early 1970s. In the 1980s, when the maximum IB14,E occurred, Δ14CRH was in a transient equilibrium with the atmosphere. The Δ14C disequilibrium between atmosphere and biosphere increased to Δ14CDIS = 20–50‰ in the mid‐1990s, before it dropped to 15–40‰ in 2005.