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The bioeconomy occupies the centre of the Green Deal, the EU’s plan to support transformative growth following the COVID-19 episode. However, parts of the EU, such as countries in Central and Eastern Europe (CEE) continue to lag behind in harnessing the potential held by the bioeconomy. This article argues that in CEE countries, where the primary and conventional bioeconomy sectors play a more important role, ‘early’ transition pathways such as improvements in productivity and practice- as well as commercialisation-oriented innovation (the do–use–interact model: DUI) are just as important as approaches based on (generally publicly supported) R&D, innovation adoption, and technology transfer (science–technology–innovation model: STI), typically associated with high-value bioindustrial applications. The argument is tested by conducting a survey of 352 experts in the region that gives an insight into the CEE macro-region’s assets with respect to deploying the bioeconomy’s potential and assessing the transition pathways relevant to the better performance of bioeconomy (primary, manufacturing, and other related) sectors. The results show the particular relevance of consolidating the primary and traditional sectors to support improvements in productivity based on the vertical and horizontal interaction typically associated with DUI, while the relevance of STI is mostly linked to advanced sectors, which are narrowly distributed across the region. The findings are relevant to policy given that the EU’s bioeconomy policy has thus far chiefly focused on STI support that better corresponds to the needs of countries at more advanced stages of developing the bioeconomy, but is less appropriate for the specific context and needs of CEE.

In the context of the European Green Deal, the manufacturing industry faces environmental challenges due to its high demand for electrical energy. Thus, measures for improving the energy efficiency or flexibility are applied to address this problem in the manufacturing industry. In order to quantify energy efficiency or flexibility potentials, it is often necessary to predict or forecast the energy consumption. This paper presents a systematic review of state-of-the-art of existing approaches to predict or forecast the energy consumption in the manufacturing industry. Seventy-two articles are classified according to the defined categories System Boundary, Modelling Technique, Modelling Focus, Modelling Horizon, Modelling Perspective, Modelling Purpose and Model Output. Based on the reviewed articles future research activities are derived.

Islands face unique challenges on their journey towards achieving carbon neutrality by the mid-century, due to the lack of energy interconnections, limited domestic energy resources, extensive fossil fuel dependence, and high load variance requiring new technologies to balance demand and supply. At the same time, these challenges can be turned into a great opportunity for economic growth and the creation of jobs with non-interconnected islands having the potential to become transition frontrunners by adopting sustainable technologies and implementing innovative solutions. This paper uses an advanced energy–economy system modeling tool (IntE3-ISL) accompanied by plausible decarbonization scenarios to assess the medium- and long-term impacts of energy transition on the energy system, emissions, economy, and society of the island of Mayotte. The model-based analysis adequately captures the specificities of Mayotte and examines the complexity, challenges, and opportunities to decarbonize the island’s non-interconnected energy system. The energy transition necessitates the adoption of ambitious climate policy measures and the extensive deployment of low- and zero-carbon technologies both in the demand and supply sides of the energy system, accounting for the unique characteristics of each individual sector, while sectoral integration is also important. To reduce emissions from hard-to-abate sectors, such as transportation and industry, the measures and technologies can include the installation and use of highly efficient equipment, the electrification of end uses (such as the widespread adoption of electric vehicles), the large roll-out of renewable energy sources, as well as the production and use of green hydrogen and synthetic fuels.

The success of the energy transition in Europe depends on the engagement of citizens and the sustainable replacement of conventional generation with renewable production. Highlights of the PAN European Technology Energy Research Approach (PANTERA) project, a H2020 coordination and support action, are presented in this paper. In broad terms, PANTERA offers a forum for actors in the smart grid to support the expansion of activities in smart grid research, demonstration, and innovation, especially in the below-average spending member states in the European Union (EU). The focus of this paper is on those activities of the project consortium related to the identification of gaps and barriers in regulations, standards, and network codes that hinder the sustainable engagement of energy citizens in the energy transition. The paper summarises the challenges to citizen engagement in the energy transit and considers the enablers that make the engagement of citizens viable, e.g., demand response (DR), renewable energy resources (RESs), and modern designs for local energy markets (LEMs). We focus on the barriers to the enablers that are explicitly and implicitly related to regulations, standards, and network codes and explore aspects of the relevant regulations and standards of the sample below-average spending member states. A specific case study of a research and demonstration project in Ireland for updating the network codes is also presented to demonstrate the ways in which member states are attempting to remove the barriers and enable citizen participation in the smart energy transition. Finally, the opportunities to foster smart grid research and innovation through shared knowledge and insights offered by the PANTERA European Interconnection for Research Innovation and Entrepreneurship (EIRIE) platform are highlighted.

The development of new climate change policies has increased the motivation to reduce energy use in buildings, as reflected by a stringent regulatory landscape. The construction industry is expected to adopt new methods and strategies to address such requirements, focusing primarily on reducing energy demand, improving process efficiency and reducing carbon emissions. However, the realisation of these emerging requirements has been constrained by the highly fragmented nature of the industry, which is often portrayed as involving a culture of adversarial relationships and risk avoidance, which is exacerbated by a linear workflow. Recurring problems include low process efficiency, delays and construction waste. Building information modelling (BIM) provides a unique opportunity to enhance building energy efficiency (EE) and to open new pathways towards a more digitalised industry and society. BIM has the potential to reduce (a) waste and carbon emissions, (b) the endemic performance gap, (c) in-use energy and (d) the total lifecycle impact. BIM also targets to improve the whole supply chain related to the design, construction as well as the management and use of the facility. However, the construction workforce is required to upgrade their skills and competencies to satisfy new requirements for delivering BIM for EE. Currently, there is a real gap between the industry expectations for employees and current training and educational programmes. There is also a set of new requirements and expectations that the construction industry needs to identify and address in order to deliver more informed BIM for EE practices. This paper provides an in-depth analysis and gap identification pertaining to the skills and competencies involved in BIM training for EE. Consultations and interviews have been used as a method to collect requirements, and a portfolio of use cases have been created and analysed to better understand existing BIM practices and to determine current limitations and gaps in BIM training. The results show that BIM can contribute to the digitalisation of the construction industry in Europe with adapted BIM training and educational programmes to deliver more informed and adapted energy strategies.

Research and Innovation (R&I) are a key part of the EU strategy towards stronger growth and the creation of more and better jobs while respecting social and climate objectives. In the last decades, improvements in costs and performance of low-carbon technologies triggered by R&I expenditures and learning-by-doing effects have increased their competitiveness compared to fossil fuel options. So, in the context of ambitious climate policies as described in the EU Green Deal, increased R&I expenditures can increase productivity and boost EU economic growth and competitiveness, especially in countries with large innovation and low-carbon manufacturing base. The analysis captures the different nature of public and private R&I, with the latter having more positive economic implications and higher efficiency as it is closer to industrial activities. Public R&D commonly focuses on immature highly uncertain technologies, which are also needed to achieve the climate neutrality target of the EU. The model-based assessment shows that a policy portfolio using part of carbon revenues for public and private R&D and development of the required skills can effectively alleviate decarbonisation costs, while promoting high value-added products and exports (e.g., low-carbon technologies), creating more high-quality jobs and contributing to climate change mitigation.

This article addresses the issue of implementing and assessing the readiness of territorial and economic systems for digital innovations in the energy industry. To achieve the goal of this research, qualitative and quantitative methods were used, including systemic and comparative analyses, a balanced scorecard (BSC), and statistical data collection and processing methods. The study resulted in a list of indicators for monitoring the readiness of the energy sector for digitization, based on which a balanced scorecard reflecting the readiness of the energy industry in countries and regional industrial complexes (RICs) was developed. A strategic map for assessing the level of readiness of the power industry for digitisation in countries and RICs was constructed using the indicator pool. The uniqueness and novelty of this study lie in the adaptation of a balanced scorecard system, aligned with a country’s or RIC’s development strategy, to determine indicators for assessing the readiness level of the considered entity for digitising the power industry. The authors establish an approach to the overall assessment and subsequent monitoring of the energy industry’s readiness for digitisation in countries worldwide and RICs.

Process planning in manufacturing today focuses on optimizing the conflicting targets of cost, quality, and time. Due to increasing social awareness and subsequent governmental regulation, environmental impact becomes a fourth major aspect. Eventually, sustainability in manufacturing ensures future competitiveness. In this paper, a framework for the planning of sustainable manufacturing is proposed. It is based on the abstraction and generalization of manufacturing resources and part descriptions, which are matched and ranked using a multi-criteria decision analysis method. Manufacturing resources provide values for cost, quality, time and environmental impacts, which multiply with their usage within a manufacturing task for a specific part. The framework is validated with a detailed modeling of a laser machine as a resource revealing benefits and optimization potential of the underlying data model. Finally, the framework is applied to a use case of a flange part with two different manufacturing strategies, i.e., laser metal-wire deposition and conventional milling. The most influential parameters regarding the environmental impacts are the raw material input, the manufacturing energy consumption and the machine production itself. In general, the framework enabled the identification of non-predetermined manufacturing possibilities and the comprehensive comparison of production resources.