Earth and Environmental Sciences

Urban heat stress in cities has intensified due to rapid urbanization (land use/land cover changes), which led to higher urban temperatures, substantially worsened outdoor thermal comfort (OTC), and increased building energy demand. Although investigations of urban heat mitigation strategies are extensive, they are not systematic or comprehensive, limiting the comparability between findings. Therefore, this study presents an integrated, transferable framework that links high-resolution local climate zone (LCZ) classification, long-term thermal hotspot identification, microclimate simulation, and building energy assessment to evaluate urban heat mitigation strategies. Using Doha as a case study, the city was classified into built (LCZs 1–6) and land cover (LCZs A–F) classes through a high-resolution LiDAR-GIS approach (overall accuracy: 95.7%), revealing substantial discrepancies relative to the global 100 m LCZ product. Analysis of Landsat imagery showed that compact urban forms are thermal hotspots, with mean summer land surface temperature reaching 43°C in compact midrise areas (LCZ 2) and 42°C in compact low-rise areas (LCZ 3). Two representative hotspot study areas (Mansoura-LCZ 2 and Salwa-LCZ 3) were selected, and their microclimates were simulated using the ENVI-met model for typical midsummer days. The model performance was evaluated against on-site measurements. Baseline simulations show severe urban thermal stress (T a > 40°C, MRT > 70°C, PET > 54°C for much of daytime). Eight mitigation scenarios based on green infrastructure and cool materials are comparatively evaluated. Green infrastructure scenarios provided consistent OTC benefits, with tree canopies producing the greatest localized cooling (T a reductions of 3–5°C, MRT reductions >15°C). Building energy simulations for July show the largest cooling demand reductions for building envelope interventions (15–25%), while tree cover scenarios produced limited savings (<3%). Overall, the study implements a cross-scale methodology for evaluating heat mitigation strategies while revealing key trade-offs in their impacts on T a , OTC, and building energy performance.

Urban systems exhibit complex dynamics that create interrelated environmental, social, and economic challenges. While most studies focus on sector-specific issues, recent approaches address urban complexity through comprehensive frameworks grounded on Systems thinking. In this context, Inclusive Climate Actions (ICAs) are adopted not only to mitigate and adapt to climate change, but also to deliver social and economic benefits. Nevertheless, the impacts of ICAs within urban systems remain largely unexplored. This study develops a digital decision-support tool based on a foresight methodology to facilitate the co-creation of urban development scenarios through ICAs , such as Nature-based Solutions, integrated within complex urban systems. The methodology constructs a causal network that defines the relationships between ICAs and pre-defined Key Performance Indicators, and operationalizes it as digital decision-support tool. Additionally, the network defines interrelationships among KPIs, highlighting synergies and trade-offs. The tool estimates the relative changes induced by the actions selected by users, both numerically and spatially. The digital decision-support tool is designed to automate the estimation process, and can be used during participatory workshops with local stakeholders, citizens, and public administrations to provide real-time information on the impacts of selected actions. This work is part of the DUT-funded GREEN-INC project.

Urbanization reshapes terrestrial carbon (C) storage by converting vegetated surfaces to impervious cover and altering biophysical and socioeconomic dynamics. We quantified the changes between 2000 and 2020 in the relative C deficit (RCD), the difference in C density between rural and urban zones, to isolate urbanization’s C storage shortfalls across 225 cities in mainland China. Nationally, declines in vegetation index and greenspace ratio strongly co-varied with higher RCD. Climate associations with RCD were nonlinear: mean annual temperature was positively associated with RCD mainly between 13.3 and 20.4 °C, whereas precipitation was positively associated with RCD above 1403 mm. Socioeconomic associations with RCD were also suggestive nonlinear patterns: GDP disparity was negatively associated with RCD approximately below 0.46 million USD km⁻² and above 3.23 million USD km⁻², but was positively associated outside these ranges. Warming was associated with lower RCD in the northeastern and southeastern regions but with higher RCD elsewhere, while the association with GDP disparity was also region-specific. These findings underscore that RCD patterns hinge on regional ecological and developmental context. Tailored strategies, combining climate-sensitive greening, blue-green infrastructure, and compact urban form, can help narrow RCD, guide urban ecosystem management and support China’s long-term C-neutrality goals.

This study explores how meso-institutional configurations shape coordination mechanisms that enable compliance with the European Union Deforestation-Free Regulation within the coffee supply chains of Brazil and Colombia. Using an institutional economics framework and a qualitative design, the study uses semi-structured interviews and institutional documents to assess how meso-institutions translate, monitor, and adapt to regulatory norms. Results show that Colombia, through the coordination of the National Federation of Coffee Growers, presents a more integrated pattern of regulatory compliance supported by legitimacy and information dissemination. Brazil operates under a decentralized structure where meso-institutions, including CECAFE and cooperatives, promote compliance through diverse, locally adapted strategies. Technological and organizational innovations emerged as an outcome of the process, with institutions deploying digital traceability platforms, georeferencing systems, and capacity-building initiatives. The findings underscore that different institutional paths can support regulatory compliance when aligned with historical governance structures. The analysis indicates that the way meso-institutions structure rule translation, information coordination, and uncertainty reduction shapes the emergence of these arrangements as adaptive responses to European regularion requirements rather than as analytically distinct types of innovation.

Urban stormwater can accumulate significant nutrients and other pollutants from the catchment, leading to water quality degradation in receiving waters. However, the impact of nutrients in urban stormwater on the ecological processes of receiving environments, particularly compared with other point and diffuse sources of nutrients, has not been well studied. Understanding how different nutrient sources affect ecological responses can improve catchment-scale nutrient management and prioritization. This study investigated how nutrients in urban stormwater impact algal growth response using standardized bioassay, and compared the response with simulated soil erosion runoff (soil slurries), effluents from tertiary-treated sewage treatment plants (STPs) and aquaculture pond effluents. A total of 43 urban stormwater samples were examined from three local government areas in South East Queensland, Australia. The study showed that all urban stormwater treatments had significantly higher algal growth responses than a control treatment without nutrient addition. Total dissolved nitrogen (TDN) was the nutrient parameter most highly correlated with the algal response for urban stormwater samples. Urban stormwater showed a similar algal response to soil slurries and aquaculture pond effluent despite differences in nitrogen forms, and a significantly higher algal response and DOC:TDN ratio than STP effluent, at the same TDN concentration. Our findings indicate that urban stormwater is an important source of nitrogen and DOC with the potential to stimulate algal growth in nitrogen limited waterways. This study suggests that more effective control of urban stormwater nutrients and organic carbon is needed to improve water quality in receiving waters.

Prior research has examined isolated aspects of artificial intelligence (AI) and circular business models (CBMs), including lifecycle optimization, stakeholder collaboration, and AI-enabled offerings. However, the literature remains fragmented and provides limited understanding of how AI reshapes circular value creation, governance, and coordination across platform ecosystems. Addressing this gap, we conduct a systematic literature review of 88 peer-reviewed articles and apply thematic analysis to develop an integrative, process-oriented framework. The analysis identifies three interdependent dimensions of AI-CBM transition: strategic reframing, AI-driven dematerialization, and ecosystem platformization, alongside socio-technical tensions that emerge through barriers, ethical and interpretive challenges, and strategic trade-offs. The findings show that AI-CBM transitions unfold through recursive cycles of experimentation, validation, and recalibration, as developments in one dimension expose misalignments in data maturity, governance arrangements, and ecosystem coordination. The framework further distinguishes when AI remains a peripheral enabler, becomes constitutive of circular value logic, or operates as ecosystem-structuring infrastructure. Conceptually, the study explains how AI reorganizes the specification, evaluation, and coordination of circular value through data-driven routines and platform infrastructures. Practically, the study develops decision heuristics and readiness conditions related to data maturity, ecosystem alignment, governance, participation, and value distribution. The study frames AI-CBM transition as a movement across socio-technical configurations that vary in structural dependence on AI and require ongoing alignment among strategic intent, technological capability, and ecosystem coordination.

Understanding wildlife responses to both anthropogenic pressures and natural environmental gradients requires large-scale and standardized surveys across broad spatial extents, enabling the identification of general patterns to assist tailored management strategies. Here, we aimed to identify the main environmental drivers shaping the occupancy patterns of widespread medium-sized mammals across multiple contrasting regions to support broad-scale inference on species-environment relationships. Using a well-replicated camera-trap dataset from 15 study areas distributed across three macrobioclimatic regions in mainland Portugal, we assessed how species occupancy was influenced by land-use composition and configuration, elevation, human footprint, seasonality, prey availability and hunting regimes, while accounting for spatial dependencies through nested random effects. Hierarchical modelling revealed that species detectability was weakly affected by covariates, whereas occupancy was primarily associated with broad-scale patterns of land-use composition and configuration, with additional effects of elevation for some species. In contrast, human footprint, hunting regimes and seasonality showed little or no detectable influence on occupancy across species at the broad spatial scale considered. Responses to land-use patterns differed among taxa, with lagomorphs showing strong but contrasting occupancy patterns along gradients of agricultural habitat structure, and carnivores exhibiting weaker and more variable responses associated with landscape heterogeneity. Overall, our results revealed consistent species-specific effects of land-use composition and configuration on broad-scale occupancy patterns of medium-sized mammals. These findings demonstrate the value of large-scale monitoring frameworks for moving beyond site-specific inference and informing transferable conservation strategies guided by land-use management across multiple regions and environmental contexts.

Oceanographic models predict relatively high rates of floating litter arrivals on shores influenced by onshore currents compared to regions with extensive offshore transport, such as Eastern Boundary Upwelling Systems. However, the lack of large-scale observations along continental coasts has prevented tests of this prediction. Volunteer participants (here, schoolchildren) sampled marine litter on continental beaches along 12,000 km of the East Pacific coast from 30°N to 45°S to assess the presence of biofouling organisms on objects with positive buoyancy. The presence of sessile biota indicates that litter items spent sufficient time in the water for these organisms to colonize, while positive buoyancy is necessary for litter to be transported by marine currents. In agreement with the predictions from Lagrangian particle simulations, higher proportions of floating litter with biofouling arrived along Central American beaches influenced by the Equatorial Current System than on the shores within Eastern Boundary Upwelling Systems. Our study highlights the considerable potential of participatory science to generate extensive, long-term, and reliable measures of floating litter and associated biota along coasts.

Source-separating wastewater systems are a potential alternative for new urban development, particularly in areas where the use and/or replacement of existing sewer infrastructure is not feasible. However, their implementation faces challenges, with low cognitive legitimacy emerging as a key barrier. This study proposes a conceptual framework to strengthen the cognitive legitimacy of source-separating wastewater systems. Workshops were held to identify the main concerns about the implementation of source-separating wastewater systems. Results from workshops were used as inputs for the literature review, and with the aid of additional interviews, a preliminary framework was proposed. The main findings enabled the proposal of four alternatives of source-separating wastewater, along with the identification of main characteristics, potential consequences, and corresponding mitigation measures. Furthermore, the study presented a relationship between these four alternatives and relevant secondary drivers. These insights served as the foundation of the proposed conceptual framework. The suggested framework aims to support stakeholders proposing source-separating wastewater systems in new developments in the planning phase by analysing different configurations and identifying the considerations behind and consequences of their implementation.