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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
Abstract
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.
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Authors (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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Full text
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- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.measurement.2022.111601
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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MEASUREMENT
no. 200,
ISSN: 0263-2241 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- 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:
- Digital Object Identifier (open in new tab) 10.1016/j.measurement.2022.111601
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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