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Air quality low-cost sensors and monitoring stations NO(2) raw dataset in Rouen (France)
This article presents a dataset comprising measurements made by co-located devices, with the aim of calibrating sensors for an upcoming in-situ use. The dataset includes hourly averaged data from 9 low-cost sensors and 2 traffic monitoring stations (thereafter named QDP and SUD3) in Rouen spanning f...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371778/ https://www.ncbi.nlm.nih.gov/pubmed/37520645 http://dx.doi.org/10.1016/j.dib.2023.109398 |
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author | Thulliez, Emma Portier, Bruno Bobbia, Michel Poggi, Jean-Michel |
author_facet | Thulliez, Emma Portier, Bruno Bobbia, Michel Poggi, Jean-Michel |
author_sort | Thulliez, Emma |
collection | PubMed |
description | This article presents a dataset comprising measurements made by co-located devices, with the aim of calibrating sensors for an upcoming in-situ use. The dataset includes hourly averaged data from 9 low-cost sensors and 2 traffic monitoring stations (thereafter named QDP and SUD3) in Rouen spanning from October 20, 2021 to March 25, 2022. In addition, the dataset is enriched by covariates measured by the sensors: temperature, relative humidity, atmospheric pressure, plus Ox and CO measures. The experiment was conducted as part of TIGA‘s call for project, and designed to have a better understanding of sensors’ drawbacks, particularly when they are moved or shut down. Knowledge about the effect of air pollution on health has gained significant attention from both the scientific community and citizens, making air quality a growing issue for urban area. As a result, the city of Rouen in Normandy, France, has prioritized air quality monitoring as a key initiative. Concurrently, several means to measure air pollutants have been made more accessible, such as the use of low-cost sensors. Those sensors offer affordability, but are known to be less accurate than monitoring stations. Thus, they need to be cautiously studied so as to be used properly. |
format | Online Article Text |
id | pubmed-10371778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103717782023-07-28 Air quality low-cost sensors and monitoring stations NO(2) raw dataset in Rouen (France) Thulliez, Emma Portier, Bruno Bobbia, Michel Poggi, Jean-Michel Data Brief Data Article This article presents a dataset comprising measurements made by co-located devices, with the aim of calibrating sensors for an upcoming in-situ use. The dataset includes hourly averaged data from 9 low-cost sensors and 2 traffic monitoring stations (thereafter named QDP and SUD3) in Rouen spanning from October 20, 2021 to March 25, 2022. In addition, the dataset is enriched by covariates measured by the sensors: temperature, relative humidity, atmospheric pressure, plus Ox and CO measures. The experiment was conducted as part of TIGA‘s call for project, and designed to have a better understanding of sensors’ drawbacks, particularly when they are moved or shut down. Knowledge about the effect of air pollution on health has gained significant attention from both the scientific community and citizens, making air quality a growing issue for urban area. As a result, the city of Rouen in Normandy, France, has prioritized air quality monitoring as a key initiative. Concurrently, several means to measure air pollutants have been made more accessible, such as the use of low-cost sensors. Those sensors offer affordability, but are known to be less accurate than monitoring stations. Thus, they need to be cautiously studied so as to be used properly. Elsevier 2023-07-11 /pmc/articles/PMC10371778/ /pubmed/37520645 http://dx.doi.org/10.1016/j.dib.2023.109398 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Data Article Thulliez, Emma Portier, Bruno Bobbia, Michel Poggi, Jean-Michel Air quality low-cost sensors and monitoring stations NO(2) raw dataset in Rouen (France) |
title | Air quality low-cost sensors and monitoring stations NO(2) raw dataset in Rouen (France) |
title_full | Air quality low-cost sensors and monitoring stations NO(2) raw dataset in Rouen (France) |
title_fullStr | Air quality low-cost sensors and monitoring stations NO(2) raw dataset in Rouen (France) |
title_full_unstemmed | Air quality low-cost sensors and monitoring stations NO(2) raw dataset in Rouen (France) |
title_short | Air quality low-cost sensors and monitoring stations NO(2) raw dataset in Rouen (France) |
title_sort | air quality low-cost sensors and monitoring stations no(2) raw dataset in rouen (france) |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371778/ https://www.ncbi.nlm.nih.gov/pubmed/37520645 http://dx.doi.org/10.1016/j.dib.2023.109398 |
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