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The long-term transition towards a low-carbon transport sector is a key strategy in Europe. This includes the replacement of fossil fuels, modal shifts towards public transport as well as higher energy efficiency in the transport sector overall. While these energy savings are likely to reduce the direct greenhouse gas emissions of transport, they also require the production of new and different vehicles. This study analyses in detail whether final energy savings in the transport sector also induce savings for material resources from nature if the production of future vehicles is considered. The results for 28 member states in 2030 indicate that energy efficiency in the transport sector leads to lower carbon emissions as well as resource use savings. However, energy-efficient transport sectors can have a significant impact on the demand for metals in Europe. An additional annual demand for 28.4 Mt of metal ores was calculated from the personal transport sector in 2030 alone. The additional metal ores from semiprecious metals (e.g., copper) amount to 12.0 Mt, from precious metals (e.g., gold) to 9.1 Mt and from other metals (e.g., lithium) to 11.7 Mt, with small savings for ferrous metal ores (-4.6 Mt).
The paper describes patterns of resource use related to German households' equipment. Using cluster analysis and material flow accounting, data on socio-demographic characteristics, and expenditures on fuel, electricity and household equipment allow for a differentiation of seven different household types. The corresponding resource use, expressed in Material Footprint per person and year, is calculated based on cradle-to-gate material flows of average household goods and the related household energy use. Our results show that patterns of resource use are mainly driven by the use of fuel and electricity and the ownership of cars. The quantified Material Footprints correlate to social status and are also linked to city size, age and household size. Affluent, established and/or younger families living in rural areas typically show the highest amounts of durables and expenditures on non-durables, thus exhibiting the highest use of natural resources.
Energy efficiency improvements have numerous benefits/impacts additional to energy and greenhouse gas savings, as has been shown and analysed e.g. in the 2014 IEA Report on "Multiple Benefits of Energy Efficiency". This paper presents the Horizon 2020-project COMBI ("Calculating and Operationalising the Multiple Benefits of Energy Efficiency in Europe"), aiming at calculating the energy and non-energy impacts that a realisation of the EU energy efficiency potential would have in 2030. The project covers the most relevant technical energy efficiency improvement actions and estimates impacts of reduced air pollution (and its effects on human health, eco-systems/crops, buildings), improved social welfare (incl. disposable income, comfort, health, productivity), saved biotic and abiotic resources, and energy system, energy security, and the macroeconomy (employment, economic growth and public budget). This paper explains how the COMBI energy savings potential in the EU 2030 is being modelled and how multiple impacts are assessed. We outline main challenges with the quantification (choice of baseline scenario, additionality of savings and impacts, context dependency and distributional issues) as well as with the aggregation of impacts (e.g. interactions and overlaps) and how the project deals with them. As research is still ongoing, this paper only gives a first impression of the order of magnitude for additional multiple impacts of energy efficiency improvements may have in Europe, where this is available to date. The paper is intended to stimulate discussion and receive feedback from the academic community on quantification approaches followed by the project.
The economic assessment of low-carbon energy options is the primary step towards the design of policy portfolios to foster the green energy economy. However, today these assessments often fall short of including important determinants of the overall cost-benefit balance of such options by not including indirect costs and benefits, even though these can be game-changing. This is often due to the lack of adequate methodologies.
The purpose of this paper is to provide a comprehensive account of the key methodological challenges to the assessment of the multiple impacts of energy options, and an initial menu of potential solutions to address these challenges.
The paper first provides evidence for the importance of the multiple impacts of energy actions in the assessment of low-carbon options.
The paper identifies a few key challenges to the evaluation of the co-impacts of low-carbon options and demonstrates that these are more complex for co-impacts than for the direct ones. Such challenges include several layers of additionality, high context dependency, and accounting for distributional effects.
The paper continues by identifying the key challenges to the aggregation of multiple impacts including the risks of overcounting while taking into account the multitude of interactions among the various co-impacts. The paper proposes an analytical framework that can help address these and frame a systematic assessment of the multiple impacts.
The German government has set itself the target of reducing the country's GHG emissions by between 80 and 95% by 2050 compared to 1990 levels. Alongside energy efficiency, renewable energy sources are set to play the main role in this transition. However, the large-scale deployment of renewable energies is expected to cause increased demand for critical mineral resources. The aim of this article is therefore to determine whether the transformation of the German energy system by 2050 ("Energiewende") may possibly be restricted by a lack of critical minerals, focusing primarily on the power sector (generating, transporting and storing electricity from renewable sources). For the relevant technologies, we create roadmaps describing a number of conceivable quantitative market developments in Germany. Estimating the current and future specific material demand of the options selected and projecting them along a range of long-term energy scenarios allows us to assess potential medium- or long-term mineral resource restrictions. The main conclusion we draw is that the shift towards an energy system based on renewable sources that is currently being pursued is principally compatible with the geological availability and supply of mineral resources. In fact, we identified certain sub-technologies as being critical with regard to potential supply risks, owing to dependencies on a small number of supplier countries and competing uses. These sub-technologies are certain wind power plants requiring neodymium and dysprosium, thin-film CIGS photovoltaic cells using indium and selenium, and large-scale redox flow batteries using vanadium. However, non-critical alternatives to these technologies do indeed exist. The likelihood of supplies being restricted can be decreased further by cooperating even more closely with companies in the supplier countries and their governments, and by establishing greater resource efficiency and recyclability as key elements of technology development.
The European Horizon 2020-project COMBI ("Calculating and Operationalising the Multiple Benefits of Energy Efficiency in Europe") aims at estimating the energy and non-energy impacts that a realisation of the EU energy efficiency potential would have in the year 2030. The project goal is to cover the most important technical potentials identified for the EU27 by 2030 and to come up with consistent estimates for the most relevant impacts: air pollution (and its effects on human health, eco-systems/crops, buildings), social welfare (including disposable income, comfort, health and productivity), biotic and abiotic resources, the energy system and energy security and the macro economy (employment, economic growth and the public budget). This paper describes the overall project research design, envisaged methodologies, the most critical methodological challenges with such an ex-ante evaluation and with aggregating the multiple impacts. The project collects data for a set of 30 energy efficiency improvement actions grouped by energy services covering all sectors and EU countries. Based on this, multiple impacts will be quantified with separate methodological approaches, following methods used in the respective literature and developing them where necessary. The paper outlines the approaches taken by COMBI: socio-economic modelling for air pollution and social welfare, resource modelling for biotic/abiotic and economically unused resources, General Equilibrium modelling for long-run macroeconomic effects and other models for short-run effects, and the LEAP model for energy system modelling. Finally, impacts will be aggregated, where possible in monetary terms. Specific challenges of this step include double-counting issues, metrics, within and cross-country/regional variability of effects and context-specificity.
Die Sustainable Development Goals (SDGs) schlagen zur Indikation verantwortungsvoller Konsum- und Produktionsstrukturen bzw. zum nachhaltigen Management und der effizienten Nutzung natürlicher Ressourcen den Material Footprint pro Kopf vor. Zudem sollen SDG-Indikatoren prinzipiell in der Lage sein, zwischen verschiedenen Bevölkerungsgruppen (etwa nach Einkommen oder Alter) unterscheiden zu können. Wir stellen einen Indikator aus der Nachhaltigkeitsstrategie NRW zum Ressourcenverbrauch des privaten Konsums auf der Grundlage von Mikrodaten vor. Der größte Ressourcenverbrauch der privaten Haushalte in NRW bleibt Wohnung, Nahrungsmittel und Verkehr vorbehalten. Dabei ist zwischen 2003 und 2013 die größte Steigerung des Ressourcenverbrauchs in Post und Telekommunikation zu verzeichnen, wobei sich insgesamt der Ressourcenverbrauch leicht reduziert hat. Der Indikator zum Ressourcenverbrauch der privaten Haushalte erfüllt die Anforderungen an Indikatoren der Sustainable Development Goals sowie der Nachhaltigkeitsstrategie des Landes NRW. Gleichzeitig empfehlen wir eine weitere Disaggregierung des Material Footprints nicht nur nach Bevölkerungsgruppen, sondern auch in Gütergruppen auf der Basis von Lebenszyklusanalysen.