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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.

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.

Historical exploitation of the Mediterranean Sea and the absence of rigorous baselines makes it difficult to evaluate the current health of the marine ecosystems and the efficacy of conservation actions at the ecosystem level. Here we establish the first current baseline and gradient of ecosystem structure of nearshore rocky reefs at the Mediterranean scale. We conducted underwater surveys in 14 marine protected areas and 18 open access sites across the Mediterranean, and across a 31-fold range of fish biomass (from 3.8 to 118 g m(-2)). Our data showed remarkable variation in the structure of rocky reef ecosystems. Multivariate analysis showed three alternative community states: (1) large fish biomass and reefs dominated by non-canopy algae, (2) lower fish biomass but abundant native algal canopies and suspension feeders, and (3) low fish biomass and extensive barrens, with areas covered by turf algae. Our results suggest that the healthiest shallow rocky reef ecosystems in the Mediterranean have both large fish and algal biomass. Protection level and primary production were the only variables significantly correlated to community biomass structure. Fish biomass was significantly larger in well-enforced no-take marine reserves, but there were no significant differences between multi-use marine protected areas (which allow some fishing) and open access areas at the regional scale. The gradients reported here represent a trajectory of degradation that can be used to assess the health of any similar habitat in the Mediterranean, and to evaluate the efficacy of marine protected areas.

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 open access book brings together a collection of cutting-edge insights into how action can and is already being taken against climate change at multiple levels of our societies, amidst growing calls for transformative and inclusive climate action. In an era of increasing recognition regarding climate and ecological breakdown, this book offers hope, inspiration and analyses for multi-level climate action, spanning varied communities, places, spaces, agents and disciplines, demonstrating how the energy and dynamism of local scales are a powerful resource in turning the tide. Interconnected yet conceptually distinct, the book’s three sections span multiple levels of analysis, interrogating diverse perspectives and practices inherent to the vivid tapestry of climate action emerging locally, nationally and internationally. Delivered in collaboration with the UK’s ‘Place-Based Climate Action Network’, chapters are drawn from a wide range of authors with varying backgrounds spread across academia, policy and practice.

The phenomena of climate change transcend all national and regional boundaries. To address this complex challenge, we must determine the areas of the country of interest, in this case, Greece, that have been most adversely affected by climate. Greece is surrounded by water, and a significant part of its GDP is derived from the marine and maritime industries, including tourism. Since the start of the IntelComp project, a Preparatory Living Lab (PLL) has been planned and delivered, feeding into the development of the IntelComp platform and the Living Lab on Climate Change Adaptation. The study's results lead to the conclusion that one of the most important challenges in tackling climate change is the decarbonisation challenge, specifically the shift to renewable energy sources and the investments that must be made. Several EU and national policy frameworks, including the European Green Deal, the Climate Law, the National Long-term Strategy for 2050 (on the Climate and Energy), highlight the decarbonisation as one of the major challenges in the climate change pledge. This will be the primary subject of the IntelComp climate change case study. PLLs also led to the identification of policy questions and useful data sources to aid the IntelComp project's launch. While previous research on co-production has primarily focused on involving citizens through public participation processes in order to gain their support, trust, and insights in structured decision-making processes, our approach opens a new channel for incorporating external knowledge into problem-solving processes. The IntelComp project will aid in policy development by providing pertinent tools co-developed with the final users that will provide insights and analysis in the field of STI (Science, Technology, Innovation) encompassing all of the Energy areas mentioned above.