Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling
This research demonstrates a methodology to integrate freely available datasets to understand the relationship between road traffic noise and cycling experiences in a medium sized city. An illustrative example of the methodology was drawn from data for Dublin, Ireland. We aggregate local environment...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024039495 |
| _version_ | 1827294004076609536 |
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| author | Rebecca Wogan John Kennedy |
| author_facet | Rebecca Wogan John Kennedy |
| author_sort | Rebecca Wogan |
| collection | DOAJ |
| description | This research demonstrates a methodology to integrate freely available datasets to understand the relationship between road traffic noise and cycling experiences in a medium sized city. An illustrative example of the methodology was drawn from data for Dublin, Ireland. We aggregate local environmental data with 81,403 Strava cycle trips, contextualised by feedback from 335 cyclists to estimate exposure levels and infer impacts on experiences and behaviours. Results demonstrate that cyclists recognise that they are subjected to increased noise levels and experience negative psychophysical consequences as a result, but they tend to downplay the impact of noise as merely a minor annoyance. Noise also impacts behaviour, most noticeably through temporal and spatial detours. Geospatial mapping was used to visualise the relationship between noise pollution and cycling activity. Estimating traffic noise levels across two cycle routes, direct vs popular detour, revealed a +10 dB(A) increase in exposure for a saving of approximately 4 min on the direct route compared to the detour. Spatial inequities in exposure levels may have serious health consequences for cyclists in a city such as Dublin. The methodology is demonstrated as suitable for policy level interventions and planning purposes. |
| first_indexed | 2024-04-24T13:48:33Z |
| format | Article |
| id | doaj.art-b33583834ba04975ba06ac851cd66e3c |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T13:48:33Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-b33583834ba04975ba06ac851cd66e3c2024-04-04T05:06:20ZengElsevierHeliyon2405-84402024-03-01106e27918Crowdsourced cycling data applications to estimate noise pollution exposure during urban cyclingRebecca Wogan0John Kennedy1Department of Mechanical, Manufacturing and Biomedical Engineering, Trinity College Dublin, University of Dublin, D02 PN40 Dublin, IrelandCorresponding author.; Department of Mechanical, Manufacturing and Biomedical Engineering, Trinity College Dublin, University of Dublin, D02 PN40 Dublin, IrelandThis research demonstrates a methodology to integrate freely available datasets to understand the relationship between road traffic noise and cycling experiences in a medium sized city. An illustrative example of the methodology was drawn from data for Dublin, Ireland. We aggregate local environmental data with 81,403 Strava cycle trips, contextualised by feedback from 335 cyclists to estimate exposure levels and infer impacts on experiences and behaviours. Results demonstrate that cyclists recognise that they are subjected to increased noise levels and experience negative psychophysical consequences as a result, but they tend to downplay the impact of noise as merely a minor annoyance. Noise also impacts behaviour, most noticeably through temporal and spatial detours. Geospatial mapping was used to visualise the relationship between noise pollution and cycling activity. Estimating traffic noise levels across two cycle routes, direct vs popular detour, revealed a +10 dB(A) increase in exposure for a saving of approximately 4 min on the direct route compared to the detour. Spatial inequities in exposure levels may have serious health consequences for cyclists in a city such as Dublin. The methodology is demonstrated as suitable for policy level interventions and planning purposes.http://www.sciencedirect.com/science/article/pii/S2405844024039495Noise pollution exposureCyclist experiencesCyclist behaviorsStravaEnvironmental health data |
| spellingShingle | Rebecca Wogan John Kennedy Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling Heliyon Noise pollution exposure Cyclist experiences Cyclist behaviors Strava Environmental health data |
| title | Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling |
| title_full | Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling |
| title_fullStr | Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling |
| title_full_unstemmed | Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling |
| title_short | Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling |
| title_sort | crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling |
| topic | Noise pollution exposure Cyclist experiences Cyclist behaviors Strava Environmental health data |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024039495 |
| work_keys_str_mv | AT rebeccawogan crowdsourcedcyclingdataapplicationstoestimatenoisepollutionexposureduringurbancycling AT johnkennedy crowdsourcedcyclingdataapplicationstoestimatenoisepollutionexposureduringurbancycling |