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.
Within the United Nations Sustainable Development 2030 agenda, sustainable growth in the marine and maritime sector needs sea water quality monitoring. This is a very demanding and expensive task which results in the sea being largely undersampled. MaDCrow is a research and development project supported by the European Regional Development Fund, that involves citizens as data collectors while aiming to improve public environmental awareness and participation in scientific research. Its goal is to create an innovative technological infrastructure for real-time acquisition, integration and access of data, thus generating knowledge on sea water quality and marine ecosystem of the Gulf of Trieste. Data acquisition is based on an autonomous and removable device, developed within the project, that can be deployed on any small size sailing boat, recreational vessel, or fishing boat. The device holds low-cost sensors to measure pH, temperature, dissolved oxygen and salinity and the hardware and software to acquire, georeference and transmit the environmental data without interfering with the activities of the boats. In this work we analyze the use, capabilities and advantages of low-cost sensors but also their limitations, comparing, with a special focus on pH, their performances with those of the traditional ones. Applying the paradigm in a highly anthropized area such as the Gulf of Trieste, which is characterized also by a very high spatial and temporal variability of environments, we point out that this new approach allows to monitor sea water quality and highlight local anomalies with a resolution and spatial and temporal coverage that was not achievable with previous procedures, but yet at very low costs. Once received, data are then processed and submitted to a mediation flow that contextualizes and disseminates them for public use on a website. The final products have been customized to reach stakeholders such as tourists, fishermen and policy makers. The availability of information understandable to everyone, while fostering environmental awareness, stimulates, at the same time, involvement and participation of citizen scientists in the initiative. In the future, while committing to enlarge the number of participants, we will extend the analysis also toward other types of sensors.
This work aims at understanding whether a citizen science-based monitoring system could be adequate to detect the effects, in terms of air quality, of solid and liquid fuel combustion for household heating. Citizen science is known to be able to improve the coverage and resolution of measurements at a very low cost. On the other hand, it also has severe limitations. Since low-cost sensors are to be used, measurements are problematic in terms of precision and accuracy. In order to test these aspects, we developed a system named COCAL that supports all the phases of air quality monitoring, from data acquisition, georeferencing, transmission, and processing up to web mapping. In this work, we focus on particulate matter. To address the limitations of the citizen science approach, we carefully tested all the parts of the system and, in particular, the performances of the low-cost sensors. We highlighted that their precision is acceptable, while their accuracy is insufficient. Measurements taken within such a paradigm cannot be used, therefore, as reference values. They can be used, instead, as relative values, in order to identify and to map trends, anomalies and hotspots. We used COCAL extensively in the city of Trieste and were able to identify different behaviors in different areas of the city. In the city center, PM values increase constantly during the day. In the rural suburbs of the city, we observed that PM values are low during the day but increase very rapidly after 5 p.m. It is important to note that, in the city center, household heating is based almost completely on natural gas. In the rural areas, household heating is generally based on wood burning stoves or liquid and solid fuel. A possible explanation of the different behavior between the two areas can then be related to commuters living in the rural areas but working in the city center. When they return home in the evening, they switch on the heating systems triggering the release of large quantities of particulate matter. We were able to map peaks of particulate matter values and highlight that they are initially located within the village centers to later propagate to the areas around them. The possibility of mapping air quality with the coverage and resolution we were able to obtain within a citizen science approach is very encouraging. This can be very helpful in understanding the impact that liquid and solid fuel combustion can have on the environment and human health. In addition, we think that this opportunity can be very important considering the current geopolitical situation where a (hopefully only temporary) shift toward pollutant fuels is expected in the near future.
Marine research is as important as very demanding since it requires expensive infrastructures and resources. Scientific institutions, on the contrary, have very limited funding so that the seas remain, still, mostly unexplored. Another serious concern is that society at large often resonates with fake news, while scientists sometimes tend to bias research with their backgrounds and paradigms. We think that all these issues can be addressed opening the process of knowledge building to the questions and needs of stakeholders and laypeople. The MaDCrow project proposed and tested several paths to attain these goals.
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