We present new advances in monitoring particulate matter (PM) in urban areas within a participatory vehicle sensor network (VSN) that exploits the use of multiple mobile low-cost IoT devices. These devices send geolocated PM measurements to an IT infrastructure and enabled us to reconstruct, in real time, the spatial and temporal distribution of pollutants in the study area in a web-based environment. The newly acquired data were integrated with independent reference measurements available from governmental environmental agencies. We deployed the infrastructure in the city of Trieste (Italy), since the beginning of 2021, with the help of several volunteers and the local transportation authority (Trieste Trasporti). By analysing the data, we delineate areas with lower air quality and identify the possible causes of these anomalies. We were able to define a belt outside the urban center where an enhanced concentration of pollutants occurs due to a higher flux of vehicular traffic that tends to jam there. Overall, our results demonstrate that this approach can be helpful in supporting urban planning and can also stimulate the community to reflect on how they can improve air quality in the area they live by reducing the use of private cars in favour of more widespread public transportation usage.

Marine life can be severely affected by anthropogenic underwater noise. This latter increased proportionally to the rise of human activities such as maritime traffic, marine civil engineering works, oil- and gas-related activities or offshore wind farms; so much so that, currently, it can be considered a threat to the environment. Assessing underwater noise requires quite some investments both in personnel and instrumentation. If this is affordable by several governmental and scientific organizations, this cannot be extended straightforwardly to all research initiatives or to developing countries. In addition, time and geographic coverage of monitoring can also be significantly limited by the costs of multiple installations. We explore the possibility to use a solution based on off-the-shelf and low-cost technologies combined with a scalable infrastructure developed with open-source tools only. The perspective to avoid proprietary solutions allows great flexibility in extending the current paradigm toward real-time transmission, processing, and web-based data access. Our solution has been deployed at sea in November 2020 and is providing data continuously ever since. First results from the analysis of these data allowed us to highlight several interesting abiotic and anthropogenic temporal patterns.

Large amounts of vintage seismic data were rescued and disseminated in an internal project of the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS). Such types of data would be very difficult to acquire today because they cover many areas that are currently subject to restrictions in obtaining exploration permits. The datasets extend over large geographical areas, covering large geological structures and would be very expensive to acquire today. Additionally, these data are particularly interesting because they were acquired using a high-energy source (dynamite) that would be difficult to obtain permission to use today. Therefore the recovery of these data could be very interesting for both the scientific and commercial communities. The urgency of rescuing tapes before degradation, and scanning and converting the paper sections into a usable form was the main focus, but, at the same time, the project looked ahead and attempted to address possible future exploitation of these data. To this end, considering how end users are likely to search for and use data, a full processing path that goes beyond recovery to consider other aspects was developed. The other concerns integrated into this process are•data enhancement, to overcome data limitations due to the older technology used during acquisition;•data integration, to consolidate different data types within the same data space, and•data discovery, for which a specific web based framework named SNAP (Seismic data Network Access Point) was developed that allows end users to search, locate and preview the data