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1.
Sensors (Basel) ; 21(5)2021 Mar 08.
Artículo en Inglés | MEDLINE | ID: mdl-33800192

RESUMEN

The World Health Organization has estimated that air pollution is a major threat to health, causing approximately nine million premature deaths every year. Each individual has, over their lifetime, a unique exposure to air pollution through their habits, working and living conditions. Medical research requires dedicated tools to assess and understand individual exposure to air pollution in view of investigating its health effects. This paper presents portable sensors produced by the Canarin Project that provides accessible, real time personal exposure data to particulate matter. Our primary results demonstrate the use of portable sensors for the assessment of personal exposure to the different micro-environments attended by individuals, and for inspecting the short-term effects of air pollution through the example of sleep apnea. These findings underscore the necessity of obtaining contextual data in determining environmental exposure and give perspectives for the future of air pollution sensors dedicated to medical research.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire Interior , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminantes Atmosféricos/toxicidad , Contaminación del Aire/análisis , Contaminación del Aire Interior/análisis , Exposición a Riesgos Ambientales/efectos adversos , Monitoreo del Ambiente , Humanos , Material Particulado/análisis , Material Particulado/toxicidad
2.
Toxics ; 11(3)2023 Feb 23.
Artículo en Inglés | MEDLINE | ID: mdl-36976970

RESUMEN

The Polluscope project aims to better understand the personal exposure to air pollutants in the Paris region. This article is based on one campaign from the project, which was conducted in the autumn of 2019 and involved 63 participants equipped with portable sensors (i.e., NO2, BC and PM) for one week. After a phase of data curation, analyses were performed on the results from all participants, as well as on individual participants' data for case studies. A machine learning algorithm was used to allocate the data to different environments (e.g., transportation, indoor, home, office, and outdoor). The results of the campaign showed that the participants' exposure to air pollutants depended very much on their lifestyle and the sources of pollution that may be present in the vicinity. Individuals' use of transportation was found to be associated with higher levels of pollutants, even when the time spent on transport was relatively short. In contrast, homes and offices were environments with the lowest concentrations of pollutants. However, some activities performed in indoor air (e.g., cooking) also showed a high levels of pollution over a relatively short period.

3.
Sci Total Environ ; 708: 134698, 2020 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-31791756

RESUMEN

The field of small air quality sensors is of growing interest within the scientific community, especially because this new technology is liable to improve air pollutant monitoring as well as be used for personal exposure quantification. Amongst the myriad existing devices, the performances are highly variable; this is why the sensors must be rigorously assessed before deployment, according to the intended use. This study is included in the Polluscope project; its purpose is to quantify personal exposure to air pollutants by using portable sensors. This paper designs and applies a methodology for the evaluation of portable air quality sensors to eight devices measuring PM, BC, NO2 and O3. The dedicated testing protocol includes static ambient air measurements compared with reference instruments, controlled chamber and mobility tests, as well as reproducibility evaluation. Three sensors (AE51, Cairclip and Canarin) were retained to be used for the field campaigns. The reliability of their performances were robustly quantified by using several metrics. These three devices (for a total of 36 units) were deployed to be worn by volunteers for a week. The results show the ability of sensors to discriminate between different environments (i.e., cooking, commuting or in an office). This work demonstrates, first, the ability of the three selected sensors to deliver data reliable enough to enable personal exposure estimations, and second, the robustness of this testing methodology.

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