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dc.contributor.authorJusto Alonso, Maria
dc.contributor.authorMadsen, Henrik
dc.contributor.authorLiu, Peng
dc.contributor.authorJørgensen, Rikke Bramming
dc.contributor.authorJørgensen, Thomas Berg
dc.contributor.authorChristiansen, Even Johan
dc.contributor.authorMyrvang, Olav Aleksander
dc.contributor.authorBastien, Diane
dc.contributor.authorMathisen, Hans Martin
dc.date.accessioned2023-01-03T07:50:29Z
dc.date.available2023-01-03T07:50:29Z
dc.date.created2022-08-09T10:12:12Z
dc.date.issued2022
dc.identifier.issn0360-1323
dc.identifier.urihttps://hdl.handle.net/11250/3040437
dc.description.abstractLow-cost sensors (LCS) are becoming ubiquitous in the market; however, calibration is needed before reliable use. An evaluation of the calibration of eight identical pre-calibrated formaldehyde LCS is presented here. The LCS and a reference instrument were exposed to a pollutant source(s) for the calibration measurements. After one year, some tests were repeated to check the drift and stability of calibration. This paper presents methodologies for calibration using data with significant autocorrelations. Autocorrelation in sensor measurements might be present when performing a frequent sampling. To obtain reliable results, sensor calibration methodologies must consider autocorrelation or serial correlation between subsequent measurements. Experimental design can be used to reduce the risk of highly autocorrelated measurement. Ordinary Least Squares Estimations should not be used when measurements are autocorrelated, as their central assumption is that the residuals are independent and identically distributed. Two alternative methods considering autocorrelation using a first-order Markov scaling are proposed: Maximum Likelihood and Restricted Maximum Likelihood Estimation (REML). REML has better compensations for the estimated parameters and the scaling parameters. Akaike information criterion was used to select the most significant parameters resulting in formaldehyde and temperature. The results were presented for only one of the eight sensors. According to EPA's recommendations, the tested formaldehyde LCSs were Tier III, supplementary monitoring. The LCS over-and under-estimated the values obtained by the reference sensor, but they presented very similar dynamic responses, indicating that LCS could be used to detect concentration changes after calibration.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleEvaluation of low-cost formaldehyde sensors calibrationen_US
dc.title.alternativeEvaluation of low-cost formaldehyde sensors calibrationen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.volume222en_US
dc.source.journalBuilding and Environmenten_US
dc.identifier.doi10.1016/j.buildenv.2022.109380
dc.identifier.cristin2041887
dc.relation.projectNorges forskningsråd: 257660en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal