AirHeritage Datalake: Multi-site, Multi-season, Multi Unit dataset including Fixed and Mobile Citizen science data from networked Air Quality Low-Cost Multi-Sensors devices and reference stations
Authors/Creators
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De Vito, Saverio
(Contact person)1
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D' Elia, Gerardo
(Data curator)1
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Ferlito, Sergio
(Data curator)1
- Esposito, Elena (Data curator)1
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Fattoruso, Grazia
(Data collector)1
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Del Giudice, Antonio
(Data collector)1
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Formisano, Fabrizio
(Data collector)
- Loffredo, Giuseppe (Data collector)1
- Massera, Ettore (Data collector)2
- D' Auria, Paolo (Data collector)3
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Di Francia, Girolamo
(Other)1
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1.
National Agency for New Technologies, Energy and Sustainable Economic Development
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2.
National Agency for New Technologies Energy and Sustainable Economic Development
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3.
Agenzia Regionale per la Protezione Ambientale
Description
This datalake comprises several datasets from 37 networked low cost air quality multisensors (30 mobile ENEA MONICA(tm) + 7 fixed) along with 3 (fixed) + 1 (mobile) reference stations operated by Campania Regional Envronmental Protection Agency. The datalake is organized in 3 main directories respectively related to fixed nodes, mobile nodes and nearby reference stations including a mobile laboratory used for colocation campaigns; each subdirectory include its own metadata description file.
Data, curated by Energy and Data Science Laboratory of ENEA, include multi-weeks colocation periods when low cost devices have been colocated with reference stations as well as operational periods during which sensors are deployed for fixed or mobile monitoring campaigns. Data have been recorded during 2021 and 2022 in a pervasive, multi-site, multi-seasonal deployment in Portici, a densely populated small area city (4km2, 55k + inhabitants) located 7km south of Naples, Italy.
The datalake consists in actual sensors and reference intrumentations timeseries along with metadata description files with deployment dates and location data. The dataset files include high sampling frequency raw sensor data of quality-controlled sensor network along with co-located reference stations data sets. Sensor data include electrochemical sensors data (intended target pollutants: NO2, O3, CO), Optical sensor data (PM2.5, PM10, PM1) readings along with meteorological parameters. .
Further description of sensors and reference instruments are reported in the accompanying paper (see citation request).
The dataset can be used for
- advanced (remote/universal/in field) data driven calibration strategies test or development including machine learning models
- mobile opportunistic data fusion methods development
- geomatics and data assimilation models studies
as well as low cost sensor characterization performance studies.
Notes
Data description paper (Citation Request):
S. De Vito, A. Del Giudice, G. D’Elia, E. Esposito, G. Fattoruso, S. Ferlito, F. Formisano, G. Loffredo, E. Massera, P. D’ Auria and G. Di Francia, Future Low-Cost Urban Air Quality Monitoring Networks: Lessons from the EU-UIA AirHeritage project, sumbitted to Atmosphere, available in preprints at preprints.org at https://www.preprints.org/manuscript/202408.0389/v1
Notes
Acknowleddgements
The creation of this dataset was supported by European Union through European Regional Development Fund (ERDF) under the Urban Innovation Action (UIA) scheme, project UIA-026 "AirHeritage" and under Horizon 2020 scheme, project VIDIS - Virtual Centre for distributed atmospheric sensing and reduction of pollutant pressure, grant agreement No 952433..
We would like to thank the city of Portici and, in particular, local citizens associations and schools who participated in AirHeritage measurement campaigns. We would like to thank furthermore all the project partners (UNINA. Terraria srl, Legambiente) and the MUA, the Portici municipality and, in particular, Mr. E. Morandino for support in selecting fixed sensor locations and practical arrangements, Dr. A. Palladino for administrative management, Dr. M. Minichino and the Dr. V. Cuomo, City Mayor for continuous support to the AirHeritage project implementation. FInally We thank Dr. E. Terzini - ENEA for extraordinary suppport to the proposition, implementation and dissemination of the project.
We would like to thank all participants of VIDIS project belonging to VINS (SRB), NILU (NO) and QUT (AUS) and in particular Prof.(s) M. Davidovic, M. Jovasevic-Stojanovic, A. Bartonova andd Z. Ristowski for continuous support and discussions which contributed to shape the AirHeritage Datalake dissemination.
Files
FixedNodes.zip
Additional details
Funding
References
- S. De Vito, G. D. Elia, S. Ferlito, E. Esposito, G. Piantadosi and G. D. Francia, "Remote Calibration strategies for Low Cost Air Quality Multisensors: a performance comparison," 2024 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN), Grapevine, TX, USA, 2024, pp. 1-4, doi: 10.1109/ISOEN61239.2024.10556107.
- S. De Vito, G. D' Elia, S. Ferlito, G. Di Francia, M. Davidovic, D. Stojanovic, D. Kleut, M. Jovasevic, "A Global Multiunit Calibration as a Method for Large-Scale IoT Particulate Matter Monitoring Systems Deployments," in IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-16, 2024, Art no. 2501916, doi: 10.1109/TIM.2023.3331428
- De Vito, S.; Esposito, E.; Massera, E.; Formisano, F.; Fattoruso, G.; Ferlito, S.; Del Giudice, A.; D'Elia, G.; Salvato, M.; Polichetti, T.; et al. Crowdsensing IoT Architecture for Pervasive Air Quality and Exposome Monitoring: Design, Development, Calibration, and Long-Term Validation. Sensors 2021, 21, 5219. https://doi.org/10.3390/s21155219