QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation

Autores
Diez, Sebastian; Lacy, Stuart; Urquiza, Josefina; Edwards, Pete
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The QUANT study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. The resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors’ data and calibrated products from sensor manufacturers across the three sites. This publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset’s utility and reliability.
Fil: Diez, Sebastian. Universidad del Desarrollo; Chile
Fil: Lacy, Stuart. University of York; Reino Unido
Fil: Urquiza, Josefina. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Secretaria de Posgrado.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Edwards, Pete. University of York; Reino Unido
Materia
OPEN ACCESS DATA
AIR QUALITY
LOW COST SENSOR
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/250528
Acceder
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spelling QUANT: a long-term multi-city commercial air sensor dataset for performance evaluationDiez, SebastianLacy, StuartUrquiza, JosefinaEdwards, PeteOPEN ACCESS DATAAIR QUALITYLOW COST SENSORhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1The QUANT study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. The resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors’ data and calibrated products from sensor manufacturers across the three sites. This publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset’s utility and reliability.Fil: Diez, Sebastian. Universidad del Desarrollo; ChileFil: Lacy, Stuart. University of York; Reino UnidoFil: Urquiza, Josefina. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Secretaria de Posgrado.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Edwards, Pete. University of York; Reino UnidoNature Publishing Group2024-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/250528Diez, Sebastian; Lacy, Stuart; Urquiza, Josefina; Edwards, Pete; QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation; Nature Publishing Group; Scientific Data; 11; 1; 8-2024; 1-162052-4463CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41597-024-03767-2info:eu-repo/semantics/altIdentifier/doi/10.1038/s41597-024-03767-2info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:18Zoai:ri.conicet.gov.ar:11336/250528instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:47:18.551CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
title QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
spellingShingle QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
Diez, Sebastian
OPEN ACCESS DATA
AIR QUALITY
LOW COST SENSOR
title_short QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
title_full QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
title_fullStr QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
title_full_unstemmed QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
title_sort QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
dc.creator.none.fl_str_mv Diez, Sebastian
Lacy, Stuart
Urquiza, Josefina
Edwards, Pete
author Diez, Sebastian
author_facet Diez, Sebastian
Lacy, Stuart
Urquiza, Josefina
Edwards, Pete
author_role author
author2 Lacy, Stuart
Urquiza, Josefina
Edwards, Pete
author2_role author
author
author
dc.subject.none.fl_str_mv OPEN ACCESS DATA
AIR QUALITY
LOW COST SENSOR
topic OPEN ACCESS DATA
AIR QUALITY
LOW COST SENSOR
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The QUANT study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. The resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors’ data and calibrated products from sensor manufacturers across the three sites. This publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset’s utility and reliability.
Fil: Diez, Sebastian. Universidad del Desarrollo; Chile
Fil: Lacy, Stuart. University of York; Reino Unido
Fil: Urquiza, Josefina. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Secretaria de Posgrado.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Edwards, Pete. University of York; Reino Unido
description The QUANT study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. The resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors’ data and calibrated products from sensor manufacturers across the three sites. This publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset’s utility and reliability.
publishDate 2024
dc.date.none.fl_str_mv 2024-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/250528
Diez, Sebastian; Lacy, Stuart; Urquiza, Josefina; Edwards, Pete; QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation; Nature Publishing Group; Scientific Data; 11; 1; 8-2024; 1-16
2052-4463
CONICET Digital
CONICET
url http://hdl.handle.net/11336/250528
identifier_str_mv Diez, Sebastian; Lacy, Stuart; Urquiza, Josefina; Edwards, Pete; QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation; Nature Publishing Group; Scientific Data; 11; 1; 8-2024; 1-16
2052-4463
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41597-024-03767-2
info:eu-repo/semantics/altIdentifier/doi/10.1038/s41597-024-03767-2
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Publishing Group
publisher.none.fl_str_mv Nature Publishing Group
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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