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Conflict framing-the emphasis on clashing political positions, or the reproach of one actor to another-is central in political coverage and politics. This chapter discusses its conceptualization and the subsequent consequences for citizens' political attitudes and behavior. Previous research on conflict framing has yielded mixed results, showcasing conflicts' potential to inform and engage citizens alongside fostering cynicism and polarization. In this chapter, we argue that, to understand these divergent findings, it is necessary to distinguish between different types of conflicts. To address the fragmented literature on conflict and negativity, we propose a typology of various conflict types. This typology is exemplified through a hypothetical conflict scenario centered around climate change. We evaluate the moral, political, and epistemic implications of distinct conflict frames and propose conditions under which conflicts can positively contribute to deliberative democracy. Our typology provides a starting point for further investigations into the effects of conflict frames.

Grid parity is considered the tipping point of economic competitiveness of PV systems. However, accurately determining when grid parity is achieved hinges on the reliability and precision of the methodologies and data employed. This paper systematically reviews existing methods for assessing PV grid parity, proposes a structured three-step framework for grid parity assessment, and identifies the potential enhancements for more accurate evaluation outcomes. The framework begins with the calculation of PV costs using the Levelized Cost of Electricity (LCOE) method, continues with predicting PV cost trends through learning curves, and is completed by benchmarking PV costs against electricity prices. Our findings reveal that most current PV cost calculations for grid parity primarily rely on the LCOE method, which can be enhanced by incorporating modifications for integration costs, revenues, PV performance metrics, regional-specific characteristics, and uncertainties. Moreover, learning curve models used to predict PV cost trends can be refined by tailoring learning rates and model formulations to reflect specific stages of technological development and regional differences. Additionally, the results suggest that electricity prices used in grid parity assessment can be adjusted to reflect the impact of policies and market dynamics. This comprehensive review provides a robust framework for assessing grid parity and serves as an essential reference for conducting more precise techno-economic feasibility assessment of PV systems.

The authors regret that the link to the supplementary documention was inadvertedly not included in the paper. The link to the supplementary documention is now included in this corrigendum. The authors would like to apologise for any inconvenience caused.

Climate change is a defining challenge of our time, and it disproportionally impacts young people. This poses a call to action for developmental science. How does climate change shape youth’s psychological development and well-being? Can we use our expertise to empower youth to cope with and help mitigate climate change? The emerging field of research on climate change and youth development addresses these timely questions. Here I provide a concise perspective on the field, highlighting lines of research and ideas, including our own, that have begun to develop in recent years. Climate change threatens our global society, which means that our research should be global as well. I call for coordinated, international, and cross-cultural investigation to address the big questions ahead of us and empower young people from across the globe to respond to the challenges of a warming world.

The GRAPHERGIA project collaborated to release a new scientific publication in a journal, a contribution led by our partner ESYCOM, a laboratory attached to the Université Gustave Eiffel. This paper, "Power management technologies for triboelectric nanogenerators” was published in MRS BULLETIN | VOLUME 50 • MARCH 2025. It shares research on the GRAPHERGIA project’s Work Package 4 ‘Advanced electrical modelling and efficient power management of TENGs for energy harvesting and self-powered sensing IoT applications. GRAPHERGIA’s Scientific Paper Abstract A triboelectric nanogenerator (TENG) is a device that utilizes contact electrification and electrostatic induction to convert mechanical energy into electrical energy. It enables self-powering of electronic devices by harvesting mechanical energy from the environment. Its applications include biomedical devices, wearable electronics, and Internet-of-Things (IoT) sensors. Extracting electrical energy from TENG remains challenging due to its time-varying nature and low internal capacitance. Effective power-management techniques are essential for TENG energy-harvesting systems, yet research on dedicated integrated power-conversion methods is currently limited. Given the growing interest in TENG, a comprehensive exploration of energy-harvesting systems is critically necessary. This article synthesizes and compares current advancements in triboelectric energy-harvesting systems, emphasizing strategies to enhance output power through various power-conversion techniques. Additionally, it explores techniques employed in other energy-harvesting systems to inspire innovative approaches in TENG system design. About the authors A team of researchers from France, the Netherlands and China authored this publication. These authors are: Sijun Du (Corresponding author), Delft University of Technology, Delft, Department of Microelectronics, The Netherlands Philippe Basset, ESYCOM Lab, Univ Gustave Eiffel, CNRS, Marne‑la‑Vallée, France Hengyu Guo, Chongqing University, College of Physics, Chongqing, China Dimitri Galayko, LIP6 Laboratory, Sorbonne Université, Paris, France Armine Karami, ESYCOM Lab, UnivGustave Eiffel, CNRS, Marne‑la‑Vallée, France

Extreme weather events caused by climate change can affect the energy sector in different ways. For example, extreme heat, cold spells, strong winds, or flooding may lead to increased energy demand and consumption, reduced energy production, or cause infrastructure failures and outages. Underserved communities are among those most impacted by power outages resulting from extreme weather events due to lower infrastructure investment in the areas where they live. These phenomena encompass a variety of social and technical challenges, for which we propose a new, transdisciplinary framework to explore solutions for providing clean, affordable, and resilient energy systems to vulnerable and at-risk communities. The authors consider a new approach using perspectives from engineering, hazards science, and policy studies to identify and develop solutions for the expansion of the use of solar energy production coupled with increased storage capacities in places where power outages and social vulnerability intersect.

There is an urgency to accelerate the innovation, development, and deployment of low-carbon industrial processes. Reviewing existing insights into how to achieve rapid technological change may be useful to assist this acceleration. Literature offers a set of approaches to model learning-by-doing and cost reductions, such as the learning curve methodology. However, it is debated if it can accurately describe and project cost reductions for low-carbon industrial processes. The goal of this work is threefold. First, to give more insight into what factors may explain the speed of innovation and technological change of low-carbon energy technologies. Second, to review existing approaches to model innovation and technological change of energy technologies and industrial processes. Third, to devise a framework to study technological learning of industrial processes. This work presents three main outcomes. First, we report more than 30 barriers and drivers of technological change. Second, we present a list of learning curve models and complementary methodologies to represent and/or explain these barriers and drivers. Third, we propose a framework to model technological learning of low-carbon industrial processes.

Wind power accounted for 8% of global electricity generation in 2023 and is one of the cheapest forms of low-carbon electricity. Although fully commercial, many challenges remain in achieving the required scale-up, relating to integrating wind farms into wider technical, economic, social, and natural systems. We review the main challenges, outline existing solutions, and propose future research needed to overcome existing problems. Although the techno-economic challenges of grid and market integration are seen as significant obstacles to scaling up wind power, the field is replete with solutions. In many countries, planning and permitting are immediate barriers to wind-power deployment; although solutions are emerging in the EU and several countries, the effectiveness and long-term acceptance of fast-track permissions and go-to areas remains to be seen. Environmental impacts on wildlife and recycling challenges are rising issues for which tested and scalable solutions are often still lacking, pointing to large remaining research requirements.

The urgency to combat global climate change has prompted the implementation of many regional and national policies, with the European Green Deal standing out as one of the most significant initiatives. We use the recently developed TIMES-Europe energy system model to study the pivotal role of the residential sector in achieving the ambitious energy savings goal formulated by the EU in the broad framework of its Fit-for-55 policy package. We observe improved energy efficiency in households across a set of scenarios that differ in terms of climate policy ambition and level of collaboration between European countries. We find that, by 2030, residential buildings can realize up to 3000 PJ in overall energy savings. Cross-country collaboration may yield an additional 11% reduction in residential energy consumption, which could increase to 18% when combined with dwelling ret rofitting subsidies. Our analysis of the transformation of the residential fuel mix, particularly the interplay be tween biomass and natural gas usage, reveals a trade-off between short-term energy efficiency gains and long term CO2 reduction goals. In the short run, scenarios lacking stringent climate control measures exhibit higher energy savings in comparison to those embracing ambitious climate targets. This initial difference, however, diminishes over time: energy savings from climate-compliant scenarios nearly align with those in scenarios without strict climate compliance around 2040. Scenarios lacking effective climate policy result in significant delays in decarbonizing the European residential sector. Our findings underscore the critical role of ambitious climate targets and accelerated retrofitting rates, highlighting the necessity to imminently and pro actively implement directed policy interventions.