Scientific research has been acknowledged to play a pivotal role in achieving the United Nations’ 2030 Agenda. Vice-versa, since its adoption, the 2030 Agenda has been reinvigorating the academic production on sustainable development. This study provides a systematic literature review of the most used and newly developed approaches by academic research to support the achievement of the SDGs in the EU. The results are presented by descriptive, bibliometric, and content analysis. The descriptive analysis highlights a rising interest of scholars in operationalizing the 2030 Agenda, with a growing interest at the urban level. A text-mining tool was employed to scan the most investigated SDGs in the selected papers. Major interest by scholars is devoted to environmental concerns (especially linked to SDG 13, 7, 6, 12, and 15), while social issues (e.g., SDG 4, 5, and 10) still deserve more research. The bibliometric analysis unveiled poor intra-cluster connections, highlighting the need for more transdisciplinary research. The most recurrent research fields on the SDGs in the EU are governance, circular economy, ecosystem services, urban localization, and decision making. We advise future studies to focus on gaps highlighted and adopt a system perspective, boosting Policy Coherence across governance levels and scales of implementation by looking at trade-offs and assessing context-specific priorities.
The objective of this paper is to present a methodology for the integration of a Computational Fluid Dynamics (CFD) microclimate simulation and a Geographic Information System (GIS). The first workflow involves the attribution of spatial coordinates to the point data extracted from the CFD, the implementation of an SQLite database, and the connection to the database to visualise and use information on environmental and comfort variables. The second workflow involves georeferencing the CFD raster output, attributing an ID to the point data, creating a point grid in a GIS environment, and merging these with the point data on the microclimate. For demonstration purposes, the methodology is tested on a real case study using ENVI-met and ArcGIS Pro.
The implementation of a social housing network requires the adoption of welfare policies within a shared national regulatory framework, as well as new organisational, design and community models, enabled by the pervasiveness of ICT, in order to allow a paradigm shift in the dualistic structure of the real estate market. Following an analysis conducted on several levels and the involvement of local social housing authorities, we identified guidelines that are both programmatic – in the context of policies for the home – and project-related – regarding the physical and digital space, able to foster peculiar social-care relationships. In this perspective, the integration of the domains considered (smart, community, welfare) could promote an alternative social housing network.
Atmospheric Particulate Matter (PM) is considered among the main risk factors for cardiovascular, respiratory, and carcinogenic diseases. Besides, heat waves accounted for 68% of natural hazard-related deaths in Europe between 1980 and 2017 and many climate models project a global rise in climate hazards. Environmental Monitoring (EM) is a key resource to control health determinants, addressing threats arising from unhealthy external conditions. Forecasting models may need data coming from pervasive distributed sensor networks and computational simulations. Moreover, district-scale Environmental Sensing (ES) and Environmental Modelling Simulation (EMS) may identify criticalities and specific strategies to mitigate climate risk affecting physical health. This paper compares the output from ES, by field measurements during a “climate walk” joined by more than 60 people, with EMS, by a Computational Fluid Dynamic software (CFD). The assessment has been performed on a real urban district. For on-site measurements, data were acquired by low-cost IoT-based sensors developed by the authors. For simulations, we used ENVI-met, a prognostic non-hydrostatic CFD. Potential Air Temperature and PM 10-2.5 concentration parameters have been measured and simulated on a specific winter day. Results are presented and discussed through a visualisation matrix making the comparison direct. The analysis of the results pointed out the role of ES and EMS for high-resolution scenarios assessment. Although real-time monitoring needs extensive infrastructure at the urban scale, the use of low-cost sensors and a citizen science approach could provide precise input data to support even more accurate models, towards a healthy district site-specific design perspective. This may finally contribute to achieving the Sustainable Development Goal 11.6, aiming at reducing the adverse environmental impact of cities, thus paying particular attention to air quality.
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