The Nationally Determined Contributions (NDCs) are key documents providing the starting point for increasingly ambitious ‘pledge-and-review’ cycles leading to the implementation of the Paris Agreement. However, current NDCs often lack consistent and transparent targets and indicators to ensure their in-country realisation and their monitoring, tracking, and reporting in compliance with the current climate change regime. This is particularly true for developing countries, where resources and capacity to define and implement climate action plans are still largely lacking among practitioners. To tackle this problem, this essay proposes a framework for NDCs development focusing on the practitioners’ – i.e., modellers and expert analysts – uptake of open science practices, particularly concerning open-source tools and open data, via capacity-building initiatives as a first step towards transparent and accountable NDCs delivery and implementation to the benefit of national and international climate governance. The framework is applied to the case study of Costa Rica, to test its relevance and applicability.

Rising transport emissions undermine urban sustainability goals, exposing a widening gap between climate ambition and emissions trajectories. Amid these trends, in the European Union (EU), electric vehicles account for only a very small proportion of new registrations for Light Commercial Vehicles (LCVs), below the levels seen in the passenger vehicles segment. While previous studies have investigated country-specific factors, this research adopts a macro-level perspective by examining aggregate diffusion patterns of electric Light Commercial Vehicles (eLCVs) across 27 EU member states. To identify the underlying determinants of this variation, this study employed a series of panel data regression models to evaluate how a set of socioeconomic, energy, mobility, and innovation-related variables shape eLCV diffusion and, more specifically, to assess the explanatory power of these variables. Among the models tested, the Fixed Effects Model proves to be most effective in capturing these relationships, reinforcing the value of a multifactorial approach to understanding eLCV adoption dynamics. The findings enhance the understanding of structural diffusion patterns and provide an empirical basis for better aligning policy and industry efforts with the EU’s regional decarbonisation objectives.

A key challenge for implementation of a circular economy model in manufacturing systems is the functional dependence of downstream processes on upstream byproducts. Design principles provide a framework for mapping goals to solutions by decomposing complex engineering problems into structured sets of requirements to be satisfied and embodied by design parameters and process variables. Large Language Models can computationally represent such textually-described design elements to quantify interconnections between problems, solutions, and processes. We present a Functional Digital Twin concept, powered by AI language modeling and guided by principles of manufacturing systems design, to identify functionally coupled process variables in an industrial symbiosis and automatically push alerts to stakeholders in a circular manufacturing system. Changes in byproduct composition are pushed downstream, and upstream decision-makers are guided to balance satisfying their design requirements with maintaining circularity of the system. The presented method is demonstrated in a case study of bio-based absorbent materials for intended use in disposable sanitary articles developed from byproducts of the agro-food industry.

Across industry, applications involving Artificial Intelligence are shifting from task-specific to general purpose foundation models able to perform a diverse set of previously unseen functions with minimal instruction or additional training. To develop such a foundation model for engineering design, training must be completed at a meaningful scale on artifacts of prior product development, which can be multimodal and sparsely annotated. This work presents a sequence learning framework for training a foundation model on contextual relationships between function, form, and fabrication in engineering design. This learning method is demonstrated with a case study in absorbent product design.

The ‘decade of action’ intended to accomplish the ambitious 17 Sustainable Development Goals (SDGs) faces notable challenges. Our investigation into the impact of the COVID-19 crisis on SDG progress reveals important lessons for shaping effective policy interventions to ensure resilient societies and overall well-being. Through systematic mapping and a rapid review approach, our analysis reveals that nearly 90% of the SDGs, specifically 144 targets, were adversely affected by the COVID-19 pandemic. Yet, there is a glimmer of opportunity: 66 targets stand to gain from the crisis-induced transformations, provided that the right choices are made. Achieving this goal demands a comprehensive approach and decisive leadership to steer an inclusive economic recovery that also safeguards the environment while safeguarding the environment. The intricate interplay between the ongoing planetary and post-COVID-19 crises, environmental challenges, and conflicts underscores the need for a proactive, deliberate and well-informed approach, marked by collaborative decision-making, which is imperative for effectively steering the ‘decade of action’ toward achieving the SDGs. These complex challenges demand collective, decisive action, all with the overarching aim of securing a just and sustainable future for all.

The valorisation of urban biowaste can contribute to a circular and sustainable resource management. However, biowaste valorisation is not inherently sustainable. This study employs the Sustainable Development Goals (SDGs) to investigate the sustainability implications of biowaste valorisation. A narrative literature review provided an overview of the current scientific knowledge on interactions between biowaste valorisation and selected SDG targets. Then stakeholder interviews yielded insights into such interactions in a national context. Our findings show the potential for 19 synergies and 11 trade-offs between biowaste valorisation and 20 selected SDG targets that are addressed in detail. Although the synergies outnumber the trade-offs, different context-dependencies influence the nature and strength of the interactions. We highlight three types of context-dependencies relating to governance. This study informs the scientific community and decision-makers on planning for sustainable biowaste valorisation that addresses context-dependencies. The insights can guide countries and cities at early transition stages towards biowaste valorisation.

The role of electric vehicles (EVs) in more sustainable cities is widely recognized, with their adoption increasing rapidly. Most governments have targets for continued EV adoption rate growth, and some plan to ban fossil-fuelled vehicles altogether. Yet, in most countries, including Brazil, the proportion of EVs among new vehicles sold remains low. EV adoption poses multiple technological, economic and social challenges that require targeted policy mechanisms. This study assesses policy measures to expedite EV adoption for road transport decarbonisation and sheds light on the critical role of EVs in sustainable urban development. We explore electric mobility challenges in urban areas, focusing on the case of Curitiba City in Brazil. We investigate existing challenges and barriers to policy implementation in Curitiba and successful interventions in cities worldwide to identify suitable policies for Curitiba. The study uses in-depth interviews with relevant stakeholders to examine policy tools, including financial, legal, knowledge-based, and societal instruments. The study recommends complementary instruments and measures to accelerate their adoption in Curitiba. Overall, the study's results, which identify criteria for policy design and implementation towards complete transport decarbonisation, should be valuable for decision-making in transport and mobility planning.

The circular economy (CE) model, where resources are kept "in the loop" for as long as possible through a series of reusing, remanufacturing, recycling, and recovery strategies, has been acclaimed for reducing the environmental impacts of our current economic model substantially and has therefore been supported by a wide range of policymakers as one solution to tackling climate change. However, how circular transitions in cities impact people has been rarely researched, and even less attention has been paid to the negative consequences of CE transitions.

This paper presents the findings from a social impact assessment conducted in the city of Umeå, Sweden. We identified several negative impacts of a CE transition across seven social impact categories and explored three areas in depth with stakeholders in the city: employment, access to services and participation. We found that the negative impacts of the CE are perceived to be limited and that the CE interventions are mainly viewed as a win-win-win outcome, i.e., a win for the environment, the economy and people. This raises questions about the level to which societal consequences have been considered and whether all relevant stakeholders, in particular civil society, have participated in the design of the city's CE strategy. Our findings can inform other cities about possible negative consequences of CE transitions and provide insights into how to incorporate different stakeholders in the CE transition process to ensure that no one is left behind.

As cities worldwide implement strategies to accelerate the transition toward a circular economy (CE), there is an increasing need for tools to monitor progress. However, a standardised metric for CE monitoring in urban areas is lacking. This study examines the potential of the EU Circular Economy Monitoring Framework (CEMF), an established indicator-based framework for measuring national- and EU-level circularity performance, as a monitoring tool for urban areas. For this purpose, available data sources that can support the framework's application at the urban level are mapped, and data quality is assessed following the pedigree matrix approach. Next, the CEMF indicators are computed for the urban area of Umeå, Sweden. The mapping showed limited availability of urban-level data, necessitating the downscaling of national-level data using proxy factors. Most available urban-level data are of high quality, while the quality of national-level data is reduced when used to compute indicators at the urban level. The application of the CEMF in Umeå indicates that there are areas where the municipality performs well, though further improvements are needed. We conclude that the CEMF has potential as a monitoring tool for urban areas. However, improvements in CEMF...s scope and data availability are recommended.