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IntroductionWith the much-needed transformation from linear to more circular resource flows, it is imperative for enterprises to understand their financial prospects. Transforming towards Product-as-a-Service (PaaS) with circular elements introduces new considerations that must be addressed to ensure profitability and sustainability. However, there is a lack of comprehensive financial assessments based on empirical cases to guide companies in assessing the lucrativeness of their transformations. This paper addresses this gap by proposing a simple-to-use and flexible financial assessment model for PaaS, helping practitioners identify the conditions necessary for financial viability from both provider and user perspectives.MethodsGrounded in transdisciplinary research, this study focuses on a construction machine manufacturer's transformation from a traditional one-off sales business model to PaaS. The transformation is analysed through the development of a life cycle costing financial assessment model that addresses relevant cost drivers.ResultsUsing discounting methods, the model can help practitioners generate scenarios to identify feasible solutions for profitable PaaS setups. Additionally, the paper presents an analytical procedure to identify conditions for a financially viable PaaS. The procedure includes scenario-based analysis that accounts for systemic changes often necessary for successfully realising PaaS.DiscussionBy following the proposed procedure, along with the financial assessment model, manufacturers can streamline their financial assessments to identify necessary changes. For the analysed case company, the modelling results indicate that it must redesign its products for PaaS to outperform its previous business model.

Using a large dataset of well-level natural gas production from Wyoming, we evaluate the respective roles played by market signals and geological characteristics in natural gas supply. While we find well-level production of natural gas is primarily determined by geological characteristics, producers respond to market signals through drilling rates and locations. Using a novel fixed effects approach based on petroleum-engineering characteristics, we confirm that production decline rates tend to be larger for wells with larger peak-production rates. We also find that the price elasticity of peak production is negative, plausibly because firms drill in less productive locations as prices increase. Finally, we show that drilling is price inelastic, although the price elasticity of drilling increased significantly when new technologies began to be adopted in Wyoming. Our results indicate that the popular view that shale wells have larger decline rates than conventional wells can be at least partially explained by the pattern of falling natural gas prices.

The shipping industry faces a large challenge as it needs to significantly lower the amounts of Green House Gas emissions. Traditionally, reducing the fuel consumption for ships has been achieved during the design stage and, after building a ship, through optimisation of ship operations. In recent years, ship efficiency improvements using Machine Learning (ML) methods are quickly progressing, facilitated by available data from remote sensing, experiments and high-fidelity simulations. The data have been successfully applied to extract intricate empirical rules that can reduce emissions thereby helping achieve green shipping. This article presents an overview of applying ML techniques to enhance ships’ sustainability. The work covers the ML fundamentals and applications in relevant areas: ship design, operational performance, and voyage planning. Suitable ML approaches are analysed and compared on a scenario basis, with their space for improvements also discussed. Meanwhile, a reminder is given that ML has many inherent uncertainties and hence should be used with caution.

Abstract Day-ahead forecasts of direct normal irradiance (DNI) from the Integrated Forecasting System (IFS), the global model of the European Centre for Medium-Range Weather Forecasts (ECMWF), are used to simulate a concentrating solar power (CSP) plant through the System Advisor Model (SAM) to assess the potential value of the IFS in the electricity market. Although DNI forecasting from the IFS still demands advances towards cloud and aerosol representation, present results show substantial improvements with the new operational radiative scheme ecRad (cycle 43R3). A relative difference of approximately 0.12% for the total annual energy availability is found between forecasts and local measurements, while approximately 10.6% is obtained for the previous version. Results of electric energy injection to the grid from a simulated linear focus parabolic-trough system shows correlations coefficients of approximately 0.87 between hourly values of electric energy based on forecasted and measured DNI, while 0.92 are obtained for the daily values. In the context of control strategy, four operational strategies are given for different weather scenarios to handle the energy management of a CSP plant, including the effect of thermal energy storage capacity. Charge and discharge operational strategies are applied accordingly to the predicted energy availability.

This is a postprint version of the Book Chapter. Information regarding the official publication is available from the link below - Copyright @ 2011 Springer Implementation of a Life Cycle Sustainability Management (LCSM) strategy can involve significant challenges because of competing or conflicting objectives between stakeholders. These differences may, if not identified and managed, hinder successful adoption of sustainability initiatives. This article proposes a conceptual framework for stakeholder management in a LCSM context. The framework identifies the key sustainability stakeholder groups and suggests strategic ambiguity as a management tool to harness dysfunctional conflict into constructive collaboration. The framework is of practical value as it can be used as a guideline by managers who wish to improve collaboration with stakeholders along the supply chain. The article also fills a gap in the academic literature where there is only limited research on sustainability stakeholder management through strategic ambiguity.

A transition from fossil to renewable energy requires the development of sustainable electric energy storage systems capable to accommodate an increasing amount of energy, at larger power and for a longer time. Flow batteries are seen as one promising technology to face this challenge. As different innovations in this field of technology are still under development, reproducible, comparable and verifiable life cycle assessment studies are crucial to providing clear evidence on the sustainability of different flow battery systems. Based on a review of 20 relevant life cycle assessment studies for different flow battery systems, published between 1999 and 2021, this contribution explored relevant methodological choices regarding the sequence of phases defined in the ISO 14,040 series: goal and scope definition, inventory analysis, impact assessment and interpretation. Inspired by good practice examples, common gaps and weaknesses were identified and recommendations for comparative life cycle assessment studies were derived. This includes suggestions for an expanded functional unit definition, a provision of more detailed and transparent reporting of LCI data while using input/output tables. Outcomes of this study are also of relevance for the amendment of the Batteries Directive 2006/66/EC, where first drafts are under revision in the European Council, including the introduction of a battery passport, which should encourage battery producers to reduce their carbon footprint and avoid problematic materials.

Large-scale muscle injury in humans initiates a complex regeneration process, as not only the muscular, but also the vascular and neuro-muscular compartments have to be repaired. Conventional therapeutic strategies often fall short of reaching the desired functional outcome, due to the inherent complexity of natural skeletal muscle. Tissue engineering offers a promising alternative treatment strategy, aiming to achieve an engineered tissue close to natural tissue composition and function, able to induce long-term, functional regeneration after in vivo implantation. This review aims to summarize the latest approaches of tissue engineering skeletal muscle, with specific attention toward fabrication, neuro-angiogenesis, multicellularity and the biochemical cues that adjuvate the regeneration process.