Achieving climate neutrality and the provision of a route to reduce greenhouse gas emissions to zero or below requires a significant shift from a focus on top-down technological solutions to a more holistic, people-centred approach. The research presented here explores the role of ecological citizenship (EC) in this shift, and specifically how a socially innovative, co-designed approach to facilitating EC and the systemic changes needed for carbon neutrality could or should take place. The paper presents EC as an evolving practice that emphasises the responsibility of individuals and communities towards ecological sustainability and social equity. The study examines how various stakeholders, such as industry practitioners, third-sector organisations, and community members, communicate, understand, and implement EC practices, projects, and solutions, using a mixed-methods approach that includes roundtable talks and workshops. As such, the study emphasises the value of user-centred, co-designed proposals that enable individuals to actively participate in positive climate action. It also looks at the opportunities and challenges of incorporating EC into wider societal and legislative norms. At the municipal, regional, and national levels, we feel the results offer useful insights into how design processes, environmental programs, and participatory governance approaches may promote more sustainable, inclusive transitions and support achieving carbon neutrality.

As digital technology continues to embed and influence everyday life, its social and environmental impacts need to be addressed seriously. This article introduces and clarifies the concept of Ecological Citizenship (EC), defining it as a form of citizenship that extends rights and duties beyond the human social sphere into ecological systems, requiring individuals, communities, and institutions to take responsibility for the environmental consequences of their digital practices. Unlike traditional forms of citizenship tied to legal or territorial boundaries, EC is grounded in shared ecological accountability and civic responsibility. We argue that EC offers a distinctive lens for shaping the evolution of a Sustainable Digital Society (SDS), where digital innovation and sustainability are co-aligned. Through theoretical analysis and case studies, this article examines how EC can support community-based, policy-led, and design-focused approaches towards digital sustainability. We look to highlight ways in which EC can be embedded in digital behaviour, infrastructure, and product design while acknowledging barriers such as the digital divide, unequal resource allocation, and adverse policy settings. This research aims to offer policymakers, technologists, and educators’ pragmatic advice for realising sustainable design, environmental literacy, and universal digital access. The study looks to argue for a more systemic reconsideration of digital development, a consideration which places environmental values at the forefront of technological progress, to ensure that digital transformation is both socially equitable and beneficial to planetary well-being.

The responsibility for sustainable futures extends beyond individual disciplines, necessitating the adoption of diverse approaches across various fields. Water pollution is at epidemic levels, valuable materials go to landfill, ocean detritus grows, many people are disconnected from green space, and biodiversity is plummeting. We need new modes of climate futures, championing citizen agency. Societies require cross-collaborative, inclusive approaches to navigate climate future challenges. We seek to foresee ‘climate futures’ that signpost challenges, unpicking (appropriate) opportunities, benefits, and pitfalls. Through an Ecological Citizenship lens, the authors traverse situations, through preferable futures. It is an entry point for transition design, creating climate tangibility surrounding our everyday lives. The article unpicks and communicates ‘preferable futures’, conceptualising how Ecological Citizenship could be deployed. We report on workshops which yielded insights from different organisational perspectives. Insights were illustrated for public audiences. Narratives navigate ecologically engaged forms of citizenship.

Buildings account for approximately 34% of global CO₂ emissions, placing the built environment at the centre of climate action. Aging social housing represents a particularly under-studied challenge: in the United Kingdom, around 78% of the building stock predates 1980, and nearly 60% of buildings carry poor energy performance ratings. Systematic retrofit planning is further hampered by building data that is incomplete and fragmented across disparate sources. This paper presents a pilot study investigating data-driven approaches to support social housing retrofit planning across several London boroughs. Using publicly accessible property datasets, computer vision training data, and street-level imagery, we fine-tuned convolutional neural networks to predict two retrofit-relevant building characteristics: wall construction type and architectural style. In-distribution accuracy reached up to 94%; however, performance declined substantially when models were evaluated against property samples provided by local councils. This highlights the generalisation challenges inherent in applying models trained on publicly accessible data to real-world contexts, and underscores the need for broader, purpose-built labelled datasets. A stakeholder workshop with representatives from local government, retrofit organisations, and industry consultancies complemented the technical findings. Discussions surfaced practical barriers to data use in the retrofit sector, including inconsistent data formats, limited inter-organisational data sharing, and a lack of coordination across the supply chain. The findings suggest that publicly accessible housing data and machine learning hold genuine promise for large-scale urban retrofit characterisation, but that realising this potential will require greater data standardisation, coordinated investment in labelled datasets, and closer collaboration across the sector.