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SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems
Low-cost air quality sensor systems can be deployed at high density, making them a significant candidate of complementary tools for improved air quality assessment. However, they still suffer from poor or unknown data quality. In this paper, we report on a unique dataset including the raw sensor dat...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220078/ https://www.ncbi.nlm.nih.gov/pubmed/37236985 http://dx.doi.org/10.1038/s41597-023-02135-w |
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author | Van Poppel, Martine Schneider, Philipp Peters, Jan Yatkin, Sinan Gerboles, Michel Matheeussen, Christina Bartonova, Alena Davila, Silvije Signorini, Marco Vogt, Matthias Dauge, Franck René Skaar, Jøran Solnes Haugen, Rolf |
author_facet | Van Poppel, Martine Schneider, Philipp Peters, Jan Yatkin, Sinan Gerboles, Michel Matheeussen, Christina Bartonova, Alena Davila, Silvije Signorini, Marco Vogt, Matthias Dauge, Franck René Skaar, Jøran Solnes Haugen, Rolf |
author_sort | Van Poppel, Martine |
collection | PubMed |
description | Low-cost air quality sensor systems can be deployed at high density, making them a significant candidate of complementary tools for improved air quality assessment. However, they still suffer from poor or unknown data quality. In this paper, we report on a unique dataset including the raw sensor data of quality-controlled sensor networks along with co-located reference data sets. Sensor data are collected using the AirSensEUR sensor system, including sensors to monitor NO, NO(2), O(3), CO, PM(2.5), PM(10), PM(1), CO(2) and meteorological parameters. In total, 85 sensor systems were deployed throughout a year in three European cities (Antwerp, Oslo and Zagreb), resulting in a dataset comprising different meteorological and ambient conditions. The main data collection included two co-location campaigns in different seasons at an Air Quality Monitoring Station (AQMS) in each city and a deployment at various locations in each city (also including locations at other AQMSs). The dataset consists of data files with sensor and reference data, and metadata files with description of locations, deployment dates and description of sensors and reference instruments. |
format | Online Article Text |
id | pubmed-10220078 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102200782023-05-28 SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems Van Poppel, Martine Schneider, Philipp Peters, Jan Yatkin, Sinan Gerboles, Michel Matheeussen, Christina Bartonova, Alena Davila, Silvije Signorini, Marco Vogt, Matthias Dauge, Franck René Skaar, Jøran Solnes Haugen, Rolf Sci Data Data Descriptor Low-cost air quality sensor systems can be deployed at high density, making them a significant candidate of complementary tools for improved air quality assessment. However, they still suffer from poor or unknown data quality. In this paper, we report on a unique dataset including the raw sensor data of quality-controlled sensor networks along with co-located reference data sets. Sensor data are collected using the AirSensEUR sensor system, including sensors to monitor NO, NO(2), O(3), CO, PM(2.5), PM(10), PM(1), CO(2) and meteorological parameters. In total, 85 sensor systems were deployed throughout a year in three European cities (Antwerp, Oslo and Zagreb), resulting in a dataset comprising different meteorological and ambient conditions. The main data collection included two co-location campaigns in different seasons at an Air Quality Monitoring Station (AQMS) in each city and a deployment at various locations in each city (also including locations at other AQMSs). The dataset consists of data files with sensor and reference data, and metadata files with description of locations, deployment dates and description of sensors and reference instruments. Nature Publishing Group UK 2023-05-26 /pmc/articles/PMC10220078/ /pubmed/37236985 http://dx.doi.org/10.1038/s41597-023-02135-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Van Poppel, Martine Schneider, Philipp Peters, Jan Yatkin, Sinan Gerboles, Michel Matheeussen, Christina Bartonova, Alena Davila, Silvije Signorini, Marco Vogt, Matthias Dauge, Franck René Skaar, Jøran Solnes Haugen, Rolf SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems |
title | SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems |
title_full | SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems |
title_fullStr | SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems |
title_full_unstemmed | SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems |
title_short | SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems |
title_sort | senseurcity: a multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220078/ https://www.ncbi.nlm.nih.gov/pubmed/37236985 http://dx.doi.org/10.1038/s41597-023-02135-w |
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