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Reaching the climate goals for the building sector requires to improve insulation and to increase air tightness of buildings in order to minimize heat loss. To achieve these goals and to prevent risks to the health of occupants and damages to the building fabric due to insufficient removal of pollutants and humidity, broad implementation of Mechanical Ventilation and Heat Recovery (MVHR) systems is crucial.
Comparable and up to date figures on the market penetration of MVHR systems across the EU are hardly available. However, figures point to only a small share of residential buildings being currently equipped with such systems (cf. Riviere et al. 2009). For the German building stock the figure is estimated to be below 5% (Händel 2011). The paper presents insights into the reasons for the slow diffusion of HRV technologies in the German building stock. It builds on the results of a recently completed research project whose central aim was to identify actor-specific and structural barriers for the diffusion of efficient ventilation systems in apartment buildings and to examine how these barriers can be addressed.
The analysis is based on 40 semi-structured expert interviews with energy consultants, HVAC craftsmen, and housing companies, as well as guided in-depth interviews with private owners of apartment buildings or apartments that were evaluated by means of qualitative content analysis. Based on the collected data, seven barrier categories were identified, each containing a range of single barriers for the diffusion of efficient ventilation systems within the residential building stock.
Results of the analysis were quantitatively validated by means of online surveys and a household survey among 1,008 households. The paper points out interdependencies within the chain of effects leading up to the investment decision of building owners. Furthermore, based on good practice examples identified within the data collection process, it proposes different measures to address these barriers.
The key objective of this deliverable is to gain insights on and assess how CE is being implemented and R&I is being funded at regional level, e.g., via the RIS3 strategy and Structural Funds. As such it sets the scope for the project and provides the background against which programmes and measures can be understood, assessed, developed and recommended in succinct tasks and work packages. The objective of this report is to provide a concise overview of the current R&I priorities, as expressed in running and newly introduced funding and legislative measures with respect to Circular Economy in European countries and regions.
On the basis of a literature research, this subtask develops a conceptional framework for a common understanding of CE within the project team and for the following work packages and tasks. After a brief introduction into the objectives and the context of a circular economy, a more elaborated look into the necessity of an explicit understanding of CE, the objectives, the spatial perspective of CE and the specific challenges within the CICERONE context will be done, in order to develop a basis for a common understanding within the project context. Circular economy can and has to be understood as an (eco-)innovation agenda. Therefore, the paper investigates the role policy has to play to support innovation for a CE transition, for creating the framework conditions and why CE has also to be build from the ground up. Finally, the paper looks from two perspectives at emerging trends and business models in a CE to sketch next steps towards the transition in a selection of central sectors. Conclusions are drawn on the basis of the insights gained by the preceding chapters.
Urban energy systems have been commonly considered to be socio-technical systems within the boundaries of an urban area. However, recent literature challenges this notion in that it urges researchers to look at the wider interactions and influences of urban energy systems wherein the socio-technical sphere is expanded to political, environmental and economic realms as well. In addition to the inter-sectoral linkages, the diverse agents and multilevel governance trends of energy sustainability in the dynamic environment of cities make the urban energy landscape a complex one. There is a strong case then for establishing a new conceptualisation of urban energy systems that builds upon these contemporary understandings of such systems. We argue that the complex systems approach can be suitable for this. In this paper, we propose a pilot framework for understanding urban energy systems using complex systems theory as an integrating plane. We review the multiple streams of urban energy literature to identify the contemporary discussions and construct this framework that can serve as a common ontological understanding for the different scholarships studying urban energy systems. We conclude the paper by highlighting the ways in which the framework can serve some of the relevant communities.
Digital platforms may yield a host of advantages in putting circular economy into effect. This paper analyses the related chances and discusses requirements of digital platforms for the realization of a circular economy. It specifically points to potential solutions offered by digital platforms for existing barriers. From there it identifies issues that need specific attendance to create economically and ecologically functional platforms. Three economically relevant perspectives are discussed for this: a management perspective, a legislative perspective and a social/systems perspective.
Reflecting trends in the academic landscape of sustainable energy using probabilistic topic modeling
(2019)
Background: Facing planetary boundaries, we need a sustainable energy system providing its life support function for society in the long-term within environmental limits. Since science plays an important role in decision-making, this study examines the thematic landscape of research on sustainable energy, which may contribute to a sustainability transformation. Understanding the structure of the research field allows for critical reflections and the identification of blind spots for advancing this field.
Methods: The study applies a text mining approach on 26533 Scopus-indexed abstracts published from 1990 to 2016 based on a latent Dirichlet allocation topic model. Models with up 1100 topics were created. Based on coherence scores and manual inspection, the model with 300 topics was selected. These statistical methods served for highlighting timely topic trends, differing thematic fields, and emerging communities in the topic network. The study critically reflects the quantitative results from a sustainability perspective.
Results: The study identifies a focus on establishing and optimizing the energy infrastructure towards 100% renewable energies through key modern technology areas: materials science, (biological) process engineering, and (digital) monitoring and control systems. Energy storage, photonic materials, nanomaterials, or biofuels belong to the topics with the strongest trends. The study identifies decreasing trends for general aspects regarding sustainable development and related economic, environmental, and political issues.
Conclusions: The discourse is latently adopting a technology-oriented paradigm focusing on renewable energy generation and is moving away from the multi-faceted concept of sustainability. The field has the potential to contribute to climate change mitigation by optimizing renewable energy systems. However, given the complexity of these systems, horizontal integration of the various valuable vertical research strands is required. Furthermore, the holistic ecological perspective considering the global scale that has originally motivated research on sustainable energy might be re-strengthened, e.g., by an integrated energy and materials perspective. Beyond considering the physical dimensions of energy systems, existing links from the currently technology-oriented discourse to the social sciences might be strengthened. For establishing sustainable energy systems, future research will not only have to target the technical energy infrastructure but put a stronger focus on issues perceivable from a holistic second-order perspective.
Estimating the sufficiency potential in buildings : the space between underdimensioned and oversized
(2019)
The emission reduction potential of energy efficiency and energy supply in buildings is estimated in various energy and climate action plans, scenarios, and potential analyses. But the third pillar of sustainability - sufficiency - is neglected in most studies.The increasing demand of space per person in the residential sector is a trend in most European countries. Its implication on energy use, demand for resources like land, building material, equipment, and waste production is enormous. Next to the ecological impact, the distribution of space has social and societal effects. Thus, sufficiency policies in the building sector complementing efficiency and energy policy are needed for a sustainable development of the European building stock.
But how can a sufficiency potential in the building sector be estimated? How much space and equipment is needed for a decent living and how much is too much? The paper proposes four areas of sufficiency in buildings: space, design and construction, equipment, and use. It presents a set of indicators, a quantitative estimate of energy savings from reduced per capita floor area, and visualises the sufficiency potential in European countries in an experimental approach. The final discussion focuses on the question: What does this mean for policy making?
Before linking emissions trading systems, there should be a good understanding of the expected economic implications: How could linking affect the development of the common allowance price, the development of emissions or industrial production, capital flows or liquidity? Answering these questions requires a multitude of data and assumptions and therefore usually the use of economic models.
This report gives an overview of various economic models that are suitable for assessing the economic effects of linking. It analyses the economic indicators relevant for the assessment of the effects of linking, formulates requirements for economic models to answer this question, discusses the advantages and disadvantages of different modelling approaches and gives an assessment of which models are suitable in principle for the assessment of linking. Five models were selected for a more detailed description: E3ME, GEM-E3, PACE, POLES, and TIMES-MARKAL.
Footprint calculators are efficient tools to monitor the environmental impact of private consumption. We present the results of an analysis of data entered into an online Material Footprint calculator undertaken to identify the socioeconomic drivers of the Material Footprint in different areas of consumption, from housing to holidaymaking. We developed regression models to reveal (1) the impact of socioeconomic characteristics on Material Footprints of private households and (2) correlations between the components of Material Footprints for different arrays of consumption. Our results show that an increasing Material Footprint in one array of consumption comes with an increasing Material Footprint in all other arrays, with the exception of housing and holidaymaking. The socioeconomic characteristics of users have a significant impact on their Material Footprints. However, this impact varies by the array of consumption. Households only exhibit generally bigger Material Footprints as a result of higher incomes and larger dwellings. We conclude that indicators which strive to monitor resource efficiency should survey disaggregated data in order to classify the resource use to different population groups and arrays of consumption.
Green Information Systems in general, and footprint calculators in particular, are promising feedback tools to assist people in adopting sustainable behaviour. Therefore, a Material Footprint model for use in an online footprint calculator was developed by identifying the most important predictors of the Material Footprint of the calculator's users. By means of statistical learning, the analysis revealed that 22 of the 95 predictors identified accounted for 74% of the variance in Material Footprints. Ten predictors out of the 95, mainly from the mobility domain, were capable of showing a prediction accuracy of 61%. The authors conclude that 22 predictors from the areas of mobility, housing and nutrition, as well as sociodemographic information, accurately predict a person's Material Footprint. The short and concise Material Footprint model may help developers and researchers to enhance their information systems with additional items while ensuring the data quality of such applications.