We use various geophysical datasets (multibeam and singlebeam echosounder data, sub-bottom profiling Chirp and sonar data and very high-resolution boomer seismic data) along with published sedimentological data and depth data from nautical charts in order to create models of the depth of the seafloor and the base of Holocene marine sediment in the Gulf of Trieste. The two models are later used in order to calculate the thickness of marine Holocene sediment which has been depositing on the Late Pleistocene alluvial plain since the Holocene transgression in the Italian and Slovenian parts of the gulf. Thicker Holocene marine sedimentary sequences averaging at around 5 m are characteristic for the southeastern part of the gulf. In other parts of the gulf the Holocene marine sedimentary cover is very thin or even absent, except in close proximity to the shoreline and fluvial sediment sources, in the area of the Trezza Grande paleodelta and above topographic depressions of the Late Pleistocene base. The presented datasets available from the OGS SNAP data repository (http://doi.org/cpz2) represent a valuable reference for a wide variety of research disciplines dealing with the dynamic Earth system in the Gulf of Trieste and could be used as a valuable tool for designing sampling and geophysical campaigns in the studied area.

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.

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