Preface to State-of-the-Art in Real-Time Air Quality Monitoring through Low-Cost Technologies-Reference-Cited by-同舟云学术

Preface to State-of-the-Art in Real-Time Air Quality Monitoring through Low-Cost Technologies

Published:2023-03-14 Issue:3 Volume:14 Page:554
ISSN:2073-4433
Container-title:Atmosphere
language:en
Short-container-title:Atmosphere

Author:

Suriano Domenico¹^ORCID

Affiliation:

1. Department for Sustainability, Brindisi Research Center, ENEA—Italian National Agency for New Technologies, Energy and Sustainable Economic Development, SS. 7 Appia, km 706, 72100 Brindisi, Italy

Abstract

Air pollution represents one of the biggest concerns worldwide [...]

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

Link

https://www.mdpi.com/2073-4433/14/3/554/pdf

Reference8 articles.

1. Park, D., Yoo, G.-W., Park, S.-H., and Lee, J.-H. (2021). Assessment and Calibration of a Low-Cost PM2.5 Sensor Using Machine Learning (HybridL STM Neural Network): Feasibility Study to Build an Air Quality Monitoring System. Atmosphere, 12.

2. Suriano, D., and Penza, M. (2022). Assessment of the Performance of a Low-Cost Air Quality Monitor in an Indoor Environment through Different Calibration Models. Atmosphere, 13.

3. Masri, S., Rea, J., and Wu, J. (2022). Use of Low-Cost Sensors to Characterize Occupational Exposure to PM2.5 Concentrations Inside an Industrial Facility in Santa Ana, CA: Results from a Worker- and Community-Led Pilot Study. Atmosphere, 13.

4. Haugen, M.J., Singh, A., Bousiotis, D., Pope, F.D., and Boies, A.M. (2022). Differentiating Semi-Volatile and Solid Particle Events Using Low-Cost Lung-Deposited Surface Area and Black Carbon Sensors. Atmosphere, 13.

5. Schalm, O., Carro, G., Lazarov, B., Jacobs, W., and Stranger, M. (2022). Reliability of Lower-Cost Sensors in the Analysis of Indoor Air Quality on Board Ships. Atmosphere, 13.

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