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 whet...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-04-01
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| Series: | Environment International |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412025002053 |
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| Summary: | 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 (PM10 and PM2.5) 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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| ISSN: | 0160-4120 |