IVL Swedish Environmental Research Institute

ivl.se
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Calibration of SO2 and NO2 Electrochemical Sensors via a Training and Testing Method in an Industrial Coastal Environment
Show others and affiliations
2022 (English)In: Sensors, E-ISSN 1424-8220, Vol. 22, no 19, p. 7281-7281Article in journal (Refereed) Published
Abstract [en]

Low-cost sensors can provide inaccurate data as temperature and humidity affect sensoraccuracy. Therefore, calibration and data correction are essential to obtain reliable measurements.This article presents a training and testing method used to calibrate a sensor module assembledfrom SO2 and NO2 electrochemical sensors (Alphasense B4 and B43F) alongside air temperature (T)and humidity (RH) sensors.

Field training and testing were conducted in the industrialized coastalarea of Quintero Bay, Chile. The raw responses of the electrochemical (mV) and T-RH sensors weresubjected to multiple linear regression (MLR) using three data segments, based on either voltage(SO2 sensor) or temperature (NO2). The resulting MLR equations were used to estimate the referenceconcentration. In the field test, calibration improved the performance of the sensors after addingT and RH in a linear model.

The most robust models for NO2 were associated with data collectedat T < 10 C (R2 = 0.85), while SO2 robust models (R2 = 0.97) were associated with data segmentscontaining higher voltages. Overall, this training and testing method reduced the bias due to T andHR in the evaluated sensors and could be replicated in similar environments to correct raw data fromlow-cost electrochemical sensors. A calibration method based on training and sensor testing afterrelocation is presented. The results show that the SO2 sensor performed better when modeled fordifferent segments of voltage data, and the NO2 sensor model performed better when calibrated fordifferent temperature data segments.

Place, publisher, year, edition, pages
IVL Svenska Miljöinstitutet, 2022. Vol. 22, no 19, p. 7281-7281
Keywords [en]
calibration; electrochemical; relocation
Identifiers
URN: urn:nbn:se:ivl:diva-4141DOI: 10.3390/s22197281OAI: oai:DiVA.org:ivl-4141DiVA, id: diva2:1727979
Note

A-rapport, A2643

Available from: 2023-01-17 Created: 2023-01-17 Last updated: 2023-01-19

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Tagle, MatiasDonoso, RodrigoLindén, JennyHallgren, FredrikSegura, Marta
By organisation
IVL Swedish Environmental Research Institute
In the same journal
Sensors

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 32 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf