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A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities
Air pollution is an important source of morbidity and mortality. It is essential to understand to what levels of air pollution citizens are exposed, especially in urban areas. Low-cost sensors are an easy-to-use option to obtain real-time air quality (AQ) data, provided that they go through specific...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002067/ https://www.ncbi.nlm.nih.gov/pubmed/36901085 http://dx.doi.org/10.3390/ijerph20054073 |
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author | Correia, Carolina Martins, Vânia Matroca, Bernardo Santana, Pedro Mariano, Pedro Almeida, Alexandre Almeida, Susana Marta |
author_facet | Correia, Carolina Martins, Vânia Matroca, Bernardo Santana, Pedro Mariano, Pedro Almeida, Alexandre Almeida, Susana Marta |
author_sort | Correia, Carolina |
collection | PubMed |
description | Air pollution is an important source of morbidity and mortality. It is essential to understand to what levels of air pollution citizens are exposed, especially in urban areas. Low-cost sensors are an easy-to-use option to obtain real-time air quality (AQ) data, provided that they go through specific quality control procedures. This paper evaluates the reliability of the ExpoLIS system. This system is composed of sensor nodes installed in buses, and a Health Optimal Routing Service App to inform the commuters about their exposure, dose, and the transport’s emissions. A sensor node, including a particulate matter (PM) sensor (Alphasense OPC-N3), was evaluated in laboratory conditions and at an AQ monitoring station. In laboratory conditions (approximately constant temperature and humidity conditions), the PM sensor obtained excellent correlations (R(2)≈1) against the reference equipment. At the monitoring station, the OPC-N3 showed considerable data dispersion. After several corrections based on the k-Köhler theory and Multiple Regression Analysis, the deviation was reduced and the correlation with the reference improved. Finally, the ExpoLIS system was installed, leading to the production of AQ maps with high spatial and temporal resolution, and to the demonstration of the Health Optimal Routing Service App as a valuable tool. |
format | Online Article Text |
id | pubmed-10002067 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100020672023-03-11 A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities Correia, Carolina Martins, Vânia Matroca, Bernardo Santana, Pedro Mariano, Pedro Almeida, Alexandre Almeida, Susana Marta Int J Environ Res Public Health Article Air pollution is an important source of morbidity and mortality. It is essential to understand to what levels of air pollution citizens are exposed, especially in urban areas. Low-cost sensors are an easy-to-use option to obtain real-time air quality (AQ) data, provided that they go through specific quality control procedures. This paper evaluates the reliability of the ExpoLIS system. This system is composed of sensor nodes installed in buses, and a Health Optimal Routing Service App to inform the commuters about their exposure, dose, and the transport’s emissions. A sensor node, including a particulate matter (PM) sensor (Alphasense OPC-N3), was evaluated in laboratory conditions and at an AQ monitoring station. In laboratory conditions (approximately constant temperature and humidity conditions), the PM sensor obtained excellent correlations (R(2)≈1) against the reference equipment. At the monitoring station, the OPC-N3 showed considerable data dispersion. After several corrections based on the k-Köhler theory and Multiple Regression Analysis, the deviation was reduced and the correlation with the reference improved. Finally, the ExpoLIS system was installed, leading to the production of AQ maps with high spatial and temporal resolution, and to the demonstration of the Health Optimal Routing Service App as a valuable tool. MDPI 2023-02-24 /pmc/articles/PMC10002067/ /pubmed/36901085 http://dx.doi.org/10.3390/ijerph20054073 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Correia, Carolina Martins, Vânia Matroca, Bernardo Santana, Pedro Mariano, Pedro Almeida, Alexandre Almeida, Susana Marta A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities |
title | A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities |
title_full | A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities |
title_fullStr | A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities |
title_full_unstemmed | A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities |
title_short | A Low-Cost Sensor System Installed in Buses to Monitor Air Quality in Cities |
title_sort | low-cost sensor system installed in buses to monitor air quality in cities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002067/ https://www.ncbi.nlm.nih.gov/pubmed/36901085 http://dx.doi.org/10.3390/ijerph20054073 |
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