Feasibility Study on the Use of NO and PM Sensors for Exposure Assessment and Indoor Source Apportionment at Fixed Locations

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2024 Sep 14

PMID 39275677

Authors

Miriam Chacon-Mateos

Erika Remy

Uta Liebers

Frank Heimann

Christian Witt

Ulrich Vogt

Affiliations

Soon will be listed here.

Abstract

Recent advances in sensor technology for air pollution monitoring open new possibilities in the field of environmental epidemiology. The low spatial resolution of fixed outdoor measurement stations and modelling uncertainties currently limit the understanding of personal exposure. In this context, air quality sensor systems (AQSSs) offer significant potential to enhance personal exposure assessment. A pilot study was conducted to investigate the feasibility of the NO sensor model B43F and the particulate matter (PM) sensor model OPC-R1, both from Alphasense (UK), for use in epidemiological studies. Seven patients with chronic obstructive pulmonary disease (COPD) or asthma had built-for-purpose sensor systems placed inside and outside of their homes at fixed locations for one month. Participants documented their indoor activities, presence in the house, window status, and symptom severity and performed a peak expiratory flow test. The potential inhaled doses of PM and NO were calculated using different data sources such as outdoor data from air quality monitoring stations, indoor data from AQSSs, and generic inhalation rates (IR) or activity-specific IR. Moreover, the relation between indoor and outdoor air quality obtained with AQSSs, an indoor source apportionment study, and an evaluation of the suitability of the AQSS data for studying the relationship between air quality and health were investigated. The results highlight the value of the sensor data and the importance of monitoring indoor air quality and activity patterns to avoid exposure misclassification. The use of AQSSs at fixed locations shows promise for larger-scale and/or long-term epidemiological studies.

References

Song J . Towards space-time modelling of PM inhalation volume with ST-exposure. Sci Total Environ. 2024; 948:174888. DOI: 10.1016/j.scitotenv.2024.174888. View

Mazaheri M, Clifford S, Yeganeh B, Viana M, Rizza V, Flament R . Investigations into factors affecting personal exposure to particles in urban microenvironments using low-cost sensors. Environ Int. 2018; 120:496-504. DOI: 10.1016/j.envint.2018.08.033. View

Bousiotis D, Alconcel L, Beddows D, Harrison R, Pope F . Monitoring and apportioning sources of indoor air quality using low-cost particulate matter sensors. Environ Int. 2023; 174:107907. DOI: 10.1016/j.envint.2023.107907. View

Lu Y . Beyond air pollution at home: Assessment of personal exposure to PM using activity-based travel demand model and low-cost air sensor network data. Environ Res. 2021; 201:111549. DOI: 10.1016/j.envres.2021.111549. View

Orellano P, Reynoso J, Quaranta N, Bardach A, Ciapponi A . Short-term exposure to particulate matter (PM and PM), nitrogen dioxide (NO), and ozone (O) and all-cause and cause-specific mortality: Systematic review and meta-analysis. Environ Int. 2020; 142:105876. DOI: 10.1016/j.envint.2020.105876. View

Vilcassim R, Thurston G . Gaps and future directions in research on health effects of air pollution. EBioMedicine. 2023; 93:104668. PMC: 10363432. DOI: 10.1016/j.ebiom.2023.104668. View

Kornartit C, Sokhi R, Burton M, Ravindra K . Activity pattern and personal exposure to nitrogen dioxide in indoor and outdoor microenvironments. Environ Int. 2009; 36(1):36-45. DOI: 10.1016/j.envint.2009.09.004. View

Jiang H, Han J, Zhu Z, Xu W, Zheng J, Zhu Y . Patient compliance with assessing and monitoring of asthma. J Asthma. 2009; 46(10):1027-31. DOI: 10.3109/02770900903229685. View

Thurston G, Kipen H, Annesi-Maesano I, Balmes J, Brook R, Cromar K . A joint ERS/ATS policy statement: what constitutes an adverse health effect of air pollution? An analytical framework. Eur Respir J. 2017; 49(1). PMC: 5751718. DOI: 10.1183/13993003.00419-2016. View

10.

Chatzidiakou L, Krause A, Han Y, Chen W, Yan L, Popoola O . Using low-cost sensor technologies and advanced computational methods to improve dose estimations in health panel studies: results of the AIRLESS project. J Expo Sci Environ Epidemiol. 2020; 30(6):981-989. DOI: 10.1038/s41370-020-0259-6. View

11.

Bertrand L, Dawkins L, Jayaratne R, Morawska L . How to choose healthier urban biking routes: CO as a proxy of traffic pollution. Heliyon. 2020; 6(6):e04195. PMC: 7305393. DOI: 10.1016/j.heliyon.2020.e04195. View

12.

Bulot F, Russell H, Rezaei M, Johnson M, Ossont S, Morris A . Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution. Sensors (Basel). 2020; 20(8). PMC: 7218914. DOI: 10.3390/s20082219. View

13.

Rajagopalan S, Brook R . THE INDOOR-OUTDOOR AIR-POLLUTION CONTINUUM AND THE BURDEN OF CARDIOVASCULAR DISEASE: AN OPPORTUNITY FOR IMPROVING GLOBAL HEALTH. Glob Heart. 2012; 7(3):207-213. PMC: 3501678. DOI: 10.1016/j.gheart.2012.06.009. View

14.

Klepeis N, Nelson W, Ott W, Robinson J, Tsang A, Switzer P . The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants. J Expo Anal Environ Epidemiol. 2001; 11(3):231-52. DOI: 10.1038/sj.jea.7500165. View

15.

Jerrett M, Donaire-Gonzalez D, Popoola O, Jones R, Cohen R, Almanza E . Validating novel air pollution sensors to improve exposure estimates for epidemiological analyses and citizen science. Environ Res. 2017; 158:286-294. DOI: 10.1016/j.envres.2017.04.023. View

16.

Amegah A . Proliferation of low-cost sensors. What prospects for air pollution epidemiologic research in Sub-Saharan Africa?. Environ Pollut. 2018; 241:1132-1137. DOI: 10.1016/j.envpol.2018.06.044. View

17.

Tonne C . A call for epidemiology where the air pollution is. Lancet Planet Health. 2018; 1(9):e355-e356. DOI: 10.1016/S2542-5196(17)30163-8. View

18.

Gordon S, Bruce N, Grigg J, Hibberd P, Kurmi O, Hubert Lam K . Respiratory risks from household air pollution in low and middle income countries. Lancet Respir Med. 2014; 2(10):823-60. PMC: 5068561. DOI: 10.1016/S2213-2600(14)70168-7. View

19.

Corlin L, Woodin M, Amaravadi H, Henderson N, Brugge D, Durant J . A field study to estimate inhalation rates for use in a particle inhalation rate exposure metric. Sci Total Environ. 2020; 696:133919. PMC: 7067691. DOI: 10.1016/j.scitotenv.2019.133919. View

20.

Tonne C, Basagana X, Chaix B, Huynen M, Hystad P, Nawrot T . New frontiers for environmental epidemiology in a changing world. Environ Int. 2017; 104:155-162. DOI: 10.1016/j.envint.2017.04.003. View