npj urban sustainability最新文献

Cities are vulnerable to heat-related health impacts due to the compounding effects of urban heat island (UHI) and rising temperatures because of climate change. Here we characterise the contextual factors exacerbating and attenuating the risk of mortality associated with high temperature in the city of Paris. Findings suggest that reducing urban heat and mitigating UHI through urban greening should be at the forefront of adaptation strategies to prevent heat-related health impacts in cities.

Household water security - safe, affordable, reliable, and acceptable water for a thriving life - is a key avenue for adapting to extreme and chronic heat, particularly in cities. We argue that household water security is far from universal in the urban Global North, resulting in uneven capacities and strategies to adapt to heat, outside and within the home. We synthesize key insights to advance water security as a central plank of urban heat justice.

Urban livability is shaped by dominant values, often economic or aesthetic, and power dynamics that often overlook the lived experiences of deprived urban area (DUA) residents. As a result, conventional livability indicators risk reinforcing existing inequalities unless these are grounded in inclusive and participatory approaches. To address this issue, we developed lightweight deep learning models - 'AI-voters' - trained on livability preferences from both DUA residents and city planners, using open-source satellite imagery. Applied in Ghana's Greater Accra Metropolitan Area, our approach reduced data requirements to map urban livability by 90% through a two-step urban form sampling strategy that enabled scalable participatory mapping. Training separate 'AI-voters' for planners and DUA residents revealed systematic differences: planners not only disagree among themselves but also consistently assign higher livability scores and overlook the preferences of DUA residents, such as avoiding coastal area exposure. The AI-voters mirrored human-voter behavior based on physical urban features such as greenery and building density, especially when trained on the preferences of DUA residents, demonstrating their potential as scalable proxies for local insights. These results highlight the importance of integrating community perspectives into AI models trained to map urban livability to expose hidden spatial inequities and promote more inclusive urban development.

In the UK, 28 million households consume 25% of the total energy and contribute to 25% of the carbon emissions. It is vital to focus on sustainability and energy efficiency within the building sector for decarbonizing purposes. However, traditional methods such as simulations or on-site inspections are time-consuming and labor-intensive. In this research, we propose a novel methodology framework for estimating building energy efficiency using only external and widely existing data. We have designed and trained an end-to-end multi-channel deep learning model utilizing high-resolution thermal infrared and optical remotely sensed images, street view images, socio-economic indicators, and building morphological data. Validated in Glasgow and Edinburgh, the model achieved F1 scores of 0.64 and 0.69. Further analyses surprisingly suggest that more deprived neighborhoods tend to have better building energy efficiency. The study highlights how widely available data and AI can provide scalable, global solutions for advancing the net-zero agenda.

The critical nexus between biodiversity loss, climate change, and societal change is increasingly intertwined, requiring coordinated action, especially in urban contexts. This study examines how urban governance operationalizes the climate-biodiversity-health nexus in four European case cities through a goals-oriented framework informed by the Planetary Health approach. We conduct a qualitative analysis of urban policy documents to assess the degree of change and level of coordination across climate mitigation, adaptation, biodiversity, and health domains. While cities have employed transformative solutions like nature-based solutions (NBS), we consistently identify policy blind spots such as fragmented mid-level targets, sectoral silos, insufficient attention to indirect emissions, and reliance on soft governance tools. We conclude by offering actionable insights for transformative urban nexus governance: mainstream transformative metrics and indicators, create new institutional innovations, integrate multi-benefit NBS across sectors, expand governance toolkits to address trade-offs, and co-create a culture of innovation, learning, co-creation and leadership.

Well-designed city actions to reduce greenhouse gas emissions can also deliver substantial near-term health co-benefits. Improved understanding and reporting of the health benefits from climate mitigation can aid efforts by cities to design and deliver healthy, equitable solutions to the climate crisis. Using global data from the 2022 CDP-ICLEI Track cities questionnaire, we analysed factors that may influence the awareness and identification of health co-benefits from climate mitigation. Actions from the transport and AFOLU sector were five to eight times more likely to report health co-benefits than other sectors, regardless of which region the action was undertaken. There was no significant difference between actions in the pre-implementation stage compared to actions that were underway. The findings highlight the need to raise awareness about the potential health benefits linked to climate mitigation among urban policymakers across all sectors to help deliver an equitable transition to a healthy, net zero future.

Measurement is essential for effective adaptation management and operation, and indicators and metrics (I&M) have a pivotal role. Surprisingly, systematic efforts to assess advances in the provision of adaptation I&M are scarce, and those that do exist often lack in-depth analysis of the types, characteristics, and applicability of the collected information. Here, we analyse 137 publications and 901 I&M sourced in the scientific literature (2007-2022) to measure adaptation to climate change in urban areas where governments are increasingly placing efforts to prepare populations and infrastructures. A lack of common terminology, standardisation, and guidelines has resulted in a field that is complex to track and understand. This complexity has led to a fragmented methodological landscape, marked by diverse, context-dependent, and occasionally conflicting approaches to the development of I&M. We argue that conventional approaches to I&M are largely inadequate and must better emphasise quantifiability, long-term assessment, and alignment with policy objectives.

Trade-offs in nature-based solutions are increasingly recognized, with novel research interrogating their justice implications. Yet, these trade-offs and justice implications remain entrenched in an anthropocentric orientation, which is problematic in ecological and ethical terms. We discuss four common assumptions on trade-offs in NBS (instrumentalism, neutrality of science, collaborative consensus, and unitemporality) and rethink them through a multispecies justice lens, maintaining that dealing with trade-offs is a form of interspecies politics.

Urbanization converts natural landscapes into impervious surfaces, altering local climate and air quality. Greening strategies are adopted to mitigate these effects, yet their effectiveness depends on land use, urban form, geography, and climate interactions. Using an air quality model with an urban canopy scheme, we evaluate how land use changes-urban expansion, agriculture, and parks-affect urban climate and chemical processes, influencing air pollutants like NO₂, O₃, VOCs, and PMs. Applied to future land-use scenarios in the Metropolitan Area of Barcelona, our results show that a 45-55% increase in urbanization raises surface temperatures and consequently evening O₃ levels by up to 8%. Replacing 6-10% of urban land and 30-40% of natural vegetation areas into agriculture reduces O₃ by up to 10%, but increases NH₃ (up to 90%) and aerosols (up to 12%). Doubling urban green spaces reduce NO₂ (up to 3%) and increases O₃ (up to 5%) and SOA (up to 14%). Our study emphasizes the trade-offs of urban greening and the need for integrated planning to improve air quality.

Urban temperatures are rising, and urban trees can help mitigate the consequences of heat stress. However, the influence of water availability on the evaporative cooling efficiency of trees across diverse urban settings remains insufficiently understood. We modelled how varying soil moisture, built environment and tree amounts affect human thermal comfort. Our results show that increasing tree cover and maintaining high soil moisture through irrigation can generate areas of 'no thermal stress' in Zurich during an average summer day, primarily via direct soil evaporation and in less dense Local Climate Zones. In denser built environments and without enough soil moisture, achieving such thermal comfort proved more challenging. On extreme summer days, however, even extensive tree planting and full irrigation were insufficient to alleviate heat stress, indicating the need for additional adaptation strategies. Our study underscores the critical but limited role of tree planting and water management in mitigating urban heat, offering practical recommendations for green infrastructure managers.