Version 1
: Received: 2 August 2024 / Approved: 6 August 2024 / Online: 6 August 2024 (07:16:15 CEST)
How to cite:
De Vito, S.; Del Giudice, A.; D’Elia, G.; Esposito, E.; Fattoruso, G.; Ferlito, S.; Formisano, F.; Loffredo, G.; Massera, E.; D' Auria, P.; Di Francia, G. Future Low-Cost Urban Air Quality Monitoring Networks: Lessons from the EU-UIA AirHeritage Project. Preprints2024, 2024080389. https://doi.org/10.20944/preprints202408.0389.v1
De Vito, S.; Del Giudice, A.; D’Elia, G.; Esposito, E.; Fattoruso, G.; Ferlito, S.; Formisano, F.; Loffredo, G.; Massera, E.; D' Auria, P.; Di Francia, G. Future Low-Cost Urban Air Quality Monitoring Networks: Lessons from the EU-UIA AirHeritage Project. Preprints 2024, 2024080389. https://doi.org/10.20944/preprints202408.0389.v1
De Vito, S.; Del Giudice, A.; D’Elia, G.; Esposito, E.; Fattoruso, G.; Ferlito, S.; Formisano, F.; Loffredo, G.; Massera, E.; D' Auria, P.; Di Francia, G. Future Low-Cost Urban Air Quality Monitoring Networks: Lessons from the EU-UIA AirHeritage Project. Preprints2024, 2024080389. https://doi.org/10.20944/preprints202408.0389.v1
APA Style
De Vito, S., Del Giudice, A., D’Elia, G., Esposito, E., Fattoruso, G., Ferlito, S., Formisano, F., Loffredo, G., Massera, E., D' Auria, P., & Di Francia, G. (2024). Future Low-Cost Urban Air Quality Monitoring Networks: Lessons from the EU-UIA AirHeritage Project. Preprints. https://doi.org/10.20944/preprints202408.0389.v1
Chicago/Turabian Style
De Vito, S., Paolo D' Auria and Girolamo Di Francia. 2024 "Future Low-Cost Urban Air Quality Monitoring Networks: Lessons from the EU-UIA AirHeritage Project" Preprints. https://doi.org/10.20944/preprints202408.0389.v1
Abstract
The last decade has seen a significant growth in low-cost air quality monitoring systems (LCAQMS) adoption, mostly driven by the spatial density limitations of traditional regulatory grade networks which restrict their effectiveness in several settings. The EU's regulatory framework advise for deploying one air quality monitoring unit per roughly 170,000 people or 15 square kilometers which is insufficient for capturing high spatio-temporal variance in complex urban scenarios. Often these settings are characterized by distributed emissions in small roads subjected to intense cars traffic, house heating driven emissions and frequently subjected to canyon effects. The Air Heritage project in Portici, funded by the EU's Urban Innovative Actions (UIA) program, addressed these challenges by integrating low-cost sensors with traditional monitoring systems and engaging the community in pervasive measurement strategies. The project highlights the importance of individualized sensor calibration and frequent recalibrations to maintain accuracy. It also showcases the benefits of citizen science approaches, IoT infrastructures, AI components, and geostatistical sensor fusion algorithms for mobile and opportunistic air quality measurements. This paper reports on the lessons learned and experiences from the Air Heritage project, aiming to guide future implementations in similar contexts. By sharing these insights along with the gathered datalake, we aim to inform stakeholders, including researchers, public authorities, and citizens, about effective strategies for deploying and utilizing LCAQMS to enhance air quality monitoring and public awareness.
Keywords
Pervasive Air Quality Monitoring; Citizen Science; Air Quality Research Projects; Pervasive Air Quality Monitoring Dataset; Low Cost Air Quality Multisensors Systems; Artificial Intelligence; Calibration
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
