Variability in mobility-based air pollution exposure assessment: Effects of GPS tracking duration and temporal resolution of air pollution maps

Mobility-based exposure assessment of air pollution has been proposed as a potentially more valid approach than home-based assessments. However, methodological uncertainties in operationalizing mobility-based assessment may still increase inaccuracies in estimating exposures. It remains unclear whether using short-term mobility data and yearly average air pollution concentrations is reliable for estimating personal air pollution exposure. This study aimed to assess variability in exposure estimates modeled by short- and long-term global positioning system (GPS) data and air pollution maps with yearly and monthly temporal resolutions. We tracked 428 participants for a short period (14 days) with a GPS device and for a long period (several months) with a smartphone application. Exposure estimates of nitrogen dioxide, ozone, and fine particulate matter (PM<sub>10</sub> and PM<sub>2.5</sub>) were computed based on GPS data, air pollution maps, and temporal and indoor/outdoor adjustments. The concordance correlation coefficient (CCC) indicated excellent agreement (0.85-0.99) between exposure estimates based on short- and long-term GPS data from smartphones but ranged from moderate to excellent (0.57-0.99) when comparing exposure estimates based on data from different devices. Agreement between yearly and monthly map-based estimates was poor to moderate without temporal adjustment (CCC: 0-0.63) but excellent after temporal adjustment (CCC: 0.92-1.0). The findings suggest that using short-term (i.e., 7 or 14 days) GPS data and yearly average air pollution concentrations in mobility-based assessments can well represent long-term mobility and yearly averages for determining long-term exposures. However, GPS data collected via dedicated devices and smartphones may identify distinct indoor/outdoor patterns, affecting the indoor/outdoor adjustments of exposure estimates. Additionally, careful selection of using yearly or monthly maps is advised for assessing exposures within specific short periods.

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Publication Details

Journal
Environment International
Published
2025-04-01
DOI
https://doi.org/10.1016/j.envint.2025.109454
Citations
7
Primary Topic
Air Quality and Health Impacts
Type
article
Field-Weighted Citation Impact
8.40

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article

Variability in mobility-based air pollution exposure assessment: Effects of GPS tracking duration and temporal resolution of air pollution maps

Ayoung Jeong, Nicole M Probst-Hensch, Roel C.H. Vermeulen, Lai Wei et al.
7 citations
Environment International
Air Quality and Health Impacts
8.40
article

Variability in mobility-based air pollution exposure assessment: Effects of GPS tracking duration and temporal resolution of air pollution maps

Ayoung Jeong, Nicole M Probst-Hensch, Roel C.H. Vermeulen, Lai Wei, Kees de Hoogh, Benjamin Flückiger, Marco Helbich, Youchen Shen, Jelle Vlaanderen, Gerard Hoek
article en
7 citations

Abstract

Mobility-based exposure assessment of air pollution has been proposed as a potentially more valid approach than home-based assessments. However, methodological uncertainties in operationalizing mobility-based assessment may still increase inaccuracies in estimating exposures. It remains unclear whether using short-term mobility data and yearly average air pollution concentrations is reliable for estimating personal air pollution exposure. This study aimed to assess variability in exposure estimates modeled by short- and long-term global positioning system (GPS) data and air pollution maps with yearly and monthly temporal resolutions. We tracked 428 participants for a short period (14 days) with a GPS device and for a long period (several months) with a smartphone application. Exposure estimates of nitrogen dioxide, ozone, and fine particulate matter (PM<sub>10</sub> and PM<sub>2.5</sub>) were computed based on GPS data, air pollution maps, and temporal and indoor/outdoor adjustments. The concordance correlation coefficient (CCC) indicated excellent agreement (0.85-0.99) between exposure estimates based on short- and long-term GPS data from smartphones but ranged from moderate to excellent (0.57-0.99) when comparing exposure estimates based on data from different devices. Agreement between yearly and monthly map-based estimates was poor to moderate without temporal adjustment (CCC: 0-0.63) but excellent after temporal adjustment (CCC: 0.92-1.0). The findings suggest that using short-term (i.e., 7 or 14 days) GPS data and yearly average air pollution concentrations in mobility-based assessments can well represent long-term mobility and yearly averages for determining long-term exposures. However, GPS data collected via dedicated devices and smartphones may identify distinct indoor/outdoor patterns, affecting the indoor/outdoor adjustments of exposure estimates. Additionally, careful selection of using yearly or monthly maps is advised for assessing exposures within specific short periods.

Environment InternationalVol. 198
Utrecht University (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Horizon 2020 Framework Programme
Openalex Percentile: Top 2%
Air Quality and Health Impacts
8.40
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