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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
Abstrakt
Air pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited accuracy of the PM detector, the measurement data are refined using a two-stage procedure that involves elimination of the non-physical signal spikes followed by a non-linear cor-rection of the responses using a multiplicative surrogate model. The correction layer is derived from the sparse and non-uniform calibration data, i.e., a combination of the measurements from the PM monitoring station and the sensor obtained in the same location over a specified (relatively short) interval. The device and the method have been both demonstrated based on the data obtained during three measurement cam-paigns. The proposed correction scheme improves the fidelity of PM measurements by around two orders of magnitude w.r.t. the responses for which the post-processing has not been considered. Performance of the proposed surrogate-assisted technique has been favorably compared against the benchmark approaches from the literature.
Cytowania
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5
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0
Web of Science
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6
Scopus
Autorzy (8)
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Tuan-Vu Cao
- Norwegian Institute for Air Research, Oslo, Norway
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Jean-Marie Lepioufle
- Norwegian Institute for Air Research, Oslo, Norway
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Islen Vallejo
- Norwegian Institute for Air Research, Oslo, Norway
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Rune Odegard
- Norwegian Institute for Air Research, Oslo, Norway
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Hoai Phuong Ha
- University of Tromso – The Arctic University of Norway, Tromso, Norway
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Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1016/j.measurement.2022.111601
- Licencja
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otwiera się w nowej karcie
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Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuły w czasopismach
- Opublikowano w:
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MEASUREMENT
nr 200,
ISSN: 0263-2241 - Język:
- angielski
- Rok wydania:
- 2022
- Opis bibliograficzny:
- Wójcikowski M., Pankiewicz B., Bekasiewicz A., Cao T., Lepioufle J., Vallejo I., Odegard R., Phuong Ha H.: A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants// MEASUREMENT -Vol. 200, (2022), s.111601-
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1016/j.measurement.2022.111601
- Źródła finansowania:
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- Publikacja bezkosztowa
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 197 razy