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Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks
To tackle the challenge of the data accuracy issues of low-cost sensors (LCSs), the objective of this work was to obtain robust correction equations to convert LCS signals into data comparable to that of research-grade instruments using side-by-side comparisons. Limited sets of seed LCS devices, aft...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374303/ https://www.ncbi.nlm.nih.gov/pubmed/32629896 http://dx.doi.org/10.3390/s20133661 |
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author | Wang, Wen-Cheng Vincent Lung, Shih-Chun Candice Liu, Chun Hu Shui, Chen-Kai |
author_facet | Wang, Wen-Cheng Vincent Lung, Shih-Chun Candice Liu, Chun Hu Shui, Chen-Kai |
author_sort | Wang, Wen-Cheng Vincent |
collection | PubMed |
description | To tackle the challenge of the data accuracy issues of low-cost sensors (LCSs), the objective of this work was to obtain robust correction equations to convert LCS signals into data comparable to that of research-grade instruments using side-by-side comparisons. Limited sets of seed LCS devices, after laboratory evaluations, can be installed strategically in areas of interest without official monitoring stations to enable reading adjustments of other uncalibrated LCS devices to enhance the data quality of sensor networks. The robustness of these equations for LCS devices (AS-LUNG with PMS3003 sensor) under a hood and a chamber with two different burnt materials and before and after 1.5 years of field campaigns were evaluated. Correction equations with incense or mosquito coils burning inside a chamber with segmented regressions had a high R(2) of 0.999, less than 6.0% variability in the slopes, and a mean RMSE of 1.18 µg/m(3) for 0.1–200 µg/m(3) of PM(2.5), with a slightly higher RMSE for 0.1–400 µg/m(3) compared to EDM-180. Similar results were obtained for PM(1), with an upper limit of 200 µg/m(3). Sensor signals drifted 19–24% after 1.5 years in the field. Practical recommendations are given to obtain equations for Federal-Equivalent-Method-comparable measurements considering variability and cost. |
format | Online Article Text |
id | pubmed-7374303 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73743032020-08-06 Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks Wang, Wen-Cheng Vincent Lung, Shih-Chun Candice Liu, Chun Hu Shui, Chen-Kai Sensors (Basel) Article To tackle the challenge of the data accuracy issues of low-cost sensors (LCSs), the objective of this work was to obtain robust correction equations to convert LCS signals into data comparable to that of research-grade instruments using side-by-side comparisons. Limited sets of seed LCS devices, after laboratory evaluations, can be installed strategically in areas of interest without official monitoring stations to enable reading adjustments of other uncalibrated LCS devices to enhance the data quality of sensor networks. The robustness of these equations for LCS devices (AS-LUNG with PMS3003 sensor) under a hood and a chamber with two different burnt materials and before and after 1.5 years of field campaigns were evaluated. Correction equations with incense or mosquito coils burning inside a chamber with segmented regressions had a high R(2) of 0.999, less than 6.0% variability in the slopes, and a mean RMSE of 1.18 µg/m(3) for 0.1–200 µg/m(3) of PM(2.5), with a slightly higher RMSE for 0.1–400 µg/m(3) compared to EDM-180. Similar results were obtained for PM(1), with an upper limit of 200 µg/m(3). Sensor signals drifted 19–24% after 1.5 years in the field. Practical recommendations are given to obtain equations for Federal-Equivalent-Method-comparable measurements considering variability and cost. MDPI 2020-06-30 /pmc/articles/PMC7374303/ /pubmed/32629896 http://dx.doi.org/10.3390/s20133661 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Wen-Cheng Vincent Lung, Shih-Chun Candice Liu, Chun Hu Shui, Chen-Kai Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks |
title | Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks |
title_full | Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks |
title_fullStr | Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks |
title_full_unstemmed | Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks |
title_short | Laboratory Evaluations of Correction Equations with Multiple Choices for Seed Low-Cost Particle Sensing Devices in Sensor Networks |
title_sort | laboratory evaluations of correction equations with multiple choices for seed low-cost particle sensing devices in sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374303/ https://www.ncbi.nlm.nih.gov/pubmed/32629896 http://dx.doi.org/10.3390/s20133661 |
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