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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.

A major challenge in sustainability science is identifying targets that maximize ecosystem benefits to humanity while minimizing the risk of crossing critical system thresholds. One critical threshold is the biomass at which populations become so depleted that their population growth rates become negative—depensation. Here, we evaluate how the value of monitoring information increases as a natural resource spends more time near the critical threshold. This benefit emerges because higher monitoring precision promotes higher yield and a greater capacity to recover from overharvest. We show that precautionary buffers that trigger increased monitoring precision as resource levels decline may offer a way to minimize monitoring costs and maximize profits. In a world of finite resources, improving our understanding of the trade-off between precision in estimates of population status and the costs of mismanagement will benefit stakeholders that shoulder the burden of these economic and social costs.

Background: Climate change has been shown to be directly linked to multiple physiological sequelae and to impact health consequences. However, the impact of climate change on mental health globally, particularly among vulnerable populations, is less well understood. Objective: To explore the mental health impacts of climate change in vulnerable populations globally. Methods: We performed an integrative literature review to identify published articles that addressed the research question: What are the mental health impacts of climate change among vulnerable populations globally? The Vulnerable Populations Conceptual Model served as a theoretical model during the review process and data synthesis. Findings/Results: One hundred and four articles were selected for inclusion in this review after a comprehensive review of 1828 manuscripts. Articles were diverse in scope and populations addressed. Land-vulnerable persons (either due to occupation or geographic location), Indigenous persons, children, older adults, and climate migrants were among the vulnerable populations whose mental health was most impacted by climate change. The most prevalent mental health responses to climate change included solastalgia, suicidality, depression, anxiety/eco-anxiety, PTSD, substance use, insomnia, and behavioral disturbance. Conclusions: Mental health professionals including physicians, nurses, physician assistants and other healthcare providers have the opportunity to mitigate the mental health impacts of climate change among vulnerable populations through assessment, preventative education and care. An inclusive and trauma-informed response to climate-related disasters, use of validated measures of mental health, and a long-term therapeutic relationship that extends beyond the immediate consequences of climate change-related events are approaches to successful mental health care in a climate-changing world.

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.

<p>Increasing renewable energy penetrations bring complex feasibility and stability problems. Data-driven methods are applied in extracting and embedding these feasibility and stability rules in power system operations and planning. This paper presents a method of alternate support vector machine decision trees for rule extraction problems. The method has significant improvements to the classical decision-tree-based algorithms in terms of efficiency, stability and versatility. Finally, we apply the method to several power and energy system scenarios to show its effectiveness.</p>

In recent years, the accelerating climate change and intensifying natural disasters have called for more renewable, resilient, and reliable energy from more distributed sources to more diversified consumers, resulting in a pressing need for advanced situational awareness of modern smart distribution systems [...]