Assessment of controlled assistance from e-bikes as a mitigation strategy for individual PM exposure

Abstract Background While promoting active mobility and outdoor activities can benefit health (HLT), it also increases Exposure (EXP) to air pollutants, such as particulate matter (PM), due to the increased ventilation rate (VR) under physical activity. Traditional assessments of individual (IND) PM EXP involve costly equipment inaccessible to the public, but real-time low-cost sensors (LCS) are now emerging. This study presents a proof of concept to demonstrate the use of LCS for examining the real-time IND respiratory dose deposited (RDD) to PM cycling across the Brescia province. Methods An e-bike was ridden 33 times between 2022 and 2023 wearing a LCS for PM concentration [PM] linked to a GPS. Respiratory dose deposited(RDD) was calculated for six different locations within each route based on experimental PM and various VR. Results The LCS allows for the study of the spatial and temporal variability of [PM], revealing a significant difference (p < 0.01) according to the heating system operation and no significant difference (p > 0.05) depending on the location. RDD increases with [PM] and VR. Real-time and integrated RDD is calculated for routes with high (> 50 µg/m3), medium (25 µg/m3), and low (<10 µg/m3) [PM2.5]. The e-bike assistance is activated when the WHO interim target 4 of [PM] is reached to reduce VR, which corresponds to a shift to a lower physical activity intensity. The RDD calculated using the e-bike assistance over the path reduces RDD by about 23% and 11% over the high and medium [PM], while it never activates for the low [PM]. Conclusions This study demonstrates that the use of LCS allows the estimation of IND RDD, and the implementation of mitigation strategies based on controlled assistance from e-bikes would enable the reduction of PM individual EXP. Key messages • The integration of HLT data from wearable and air quality LCS enables the promotion of active mobility and outdoor activities controlling the EXP to air pollutants. • Establishing generalized guidelines based on this mitigation strategies for individual exposure reduction may also inform policy recommendations for promoting active and green mobility.

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Publication Details

Journal
European Journal of Public Health
Published
2024-10-28
DOI
https://doi.org/10.1093/eurpub/ckae144.1565
Primary Topic
Air Quality and Health Impacts
Type
article
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article

Assessment of controlled assistance from e-bikes as a mitigation strategy for individual PM exposure

Laura Borgese, Alexandra Bonardi, F. Negro
European Journal of Public Health
Air Quality and Health Impacts
article

Assessment of controlled assistance from e-bikes as a mitigation strategy for individual PM exposure

Laura Borgese, Alexandra Bonardi, F. Negro
article en

Abstract

Abstract Background While promoting active mobility and outdoor activities can benefit health (HLT), it also increases Exposure (EXP) to air pollutants, such as particulate matter (PM), due to the increased ventilation rate (VR) under physical activity. Traditional assessments of individual (IND) PM EXP involve costly equipment inaccessible to the public, but real-time low-cost sensors (LCS) are now emerging. This study presents a proof of concept to demonstrate the use of LCS for examining the real-time IND respiratory dose deposited (RDD) to PM cycling across the Brescia province. Methods An e-bike was ridden 33 times between 2022 and 2023 wearing a LCS for PM concentration [PM] linked to a GPS. Respiratory dose deposited(RDD) was calculated for six different locations within each route based on experimental PM and various VR. Results The LCS allows for the study of the spatial and temporal variability of [PM], revealing a significant difference (p < 0.01) according to the heating system operation and no significant difference (p > 0.05) depending on the location. RDD increases with [PM] and VR. Real-time and integrated RDD is calculated for routes with high (> 50 µg/m3), medium (25 µg/m3), and low (<10 µg/m3) [PM2.5]. The e-bike assistance is activated when the WHO interim target 4 of [PM] is reached to reduce VR, which corresponds to a shift to a lower physical activity intensity. The RDD calculated using the e-bike assistance over the path reduces RDD by about 23% and 11% over the high and medium [PM], while it never activates for the low [PM]. Conclusions This study demonstrates that the use of LCS allows the estimation of IND RDD, and the implementation of mitigation strategies based on controlled assistance from e-bikes would enable the reduction of PM individual EXP. Key messages • The integration of HLT data from wearable and air quality LCS enables the promotion of active mobility and outdoor activities controlling the EXP to air pollutants. • Establishing generalized guidelines based on this mitigation strategies for individual exposure reduction may also inform policy recommendations for promoting active and green mobility.

European Journal of Public HealthVol. 34(Supplement_3)
Brescia University (US), Engineering (Italy) (IT), University of Brescia (IT)
Openalex Percentile: Top 74%
Air Quality and Health Impacts
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