Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris

Gelb, Jérémy; Apparicio, Philippe

doi:10.3390/atmos11040422

Cited by 13 publications

(13 citation statements)

References 62 publications

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“…(2018b) have reported a negative association between exposure levels to noise and wind speed, with a decrease of -0.371 dB(A) for each additional km/h, and no effect with temperature. On the other hand, Apparicio et al (2016) and Gelb and Apparicio (2020) found no significant relationship between exposure to noise and temperature, humidity, and wind speed.…”

Section: Weathermentioning

confidence: 80%

Cyclists’ exposure to atmospheric and noise pollution: a systematic literature review

Gelb

2021

Transport Reviews

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Cyclists constitute a population particularly exposed to atmospheric and noise pollution in urban environments; at the same time, they contribute to its reduction. For about ten years now, more and more studies have been completed to assess cyclists' exposure, comparing this mode of transportation with others, quantifying its impacts in term of individual and collective health, understanding cyclists' perceptions regarding their exposure, etc. Though some literature reviews have examined some of these specific issues, none have yet proposed a general overview of this field of study. Therefore, this mapping literature review fills this gap by jointly analysing 205 articles and identifying elements of consensus and disagreement, as well as existing gaps. Among others, our results indicate that the cities in the South and exposure to noise are under-studied and that cyclists' ventilation is still too rarely accounted for, regardless of the type of studies. Modelling studies regarding exposure are too heterogeneous methodologically to allow a generalisation of their results. Conversely, intermodal comparison studies clearly indicate overexposure for cyclists compared to other modes. Also, health studies conclude that, either individually or collectively, the benefits of cycling surpass the costs of exposure to atmospheric pollution. The knowledge produced by this research trend remains difficult to exploit by urban planners, but the recent work done seems to offer more practical perspectives to professionals.

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Section: Weathermentioning

confidence: 80%

Cyclists’ exposure to atmospheric and noise pollution: a systematic literature review

Gelb

2021

Transport Reviews

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“…However, Gelb and Apparicio [28] observed that in Paris, France, close proximity to traffic can impose wellbeing threats to AT users via noise and air pollution. This may erode the corresponding health benefits.…”

Section: Physical and Mental Wellbeing Outcomesmentioning

confidence: 99%

Sources and Applications of Emerging Active Travel Data: A Review of the Literature

2021

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Active travel (AT) has the potential to integrate with, or in some cases substitute for, trips taken by motorized transportation. In this paper we review relevant research on AT outcomes to address the potential of AT and emerging data sources in supporting the transport paradigm shift toward AT. Our analysis identifies physical, mental, built and physical environmental, monetary, and societal outcomes. Traditional methods used to acquire AT data can be divided into manual methods that require substantial user input and automated methods that can be employed for a lengthier period and are more resilient to inclement weather. Due to the proliferation of information and communication technology, emerging data sources are prevailing and can be grouped into social fitness networks, in-house developed apps, participatory mapping, imagery, bike sharing systems, social media, and other types. We assess the emerging data sources in terms of their applications and potential limitations. Furthermore, we identify developing policies and interventions, the potential of imagery, focusing on non-cycling modes and addressing data biases. Finally, we discuss the challenges of data ownership within emerging AT data and the corresponding directions for future work.

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“…To achieve the first objective, three Bayesian models were constructed using the brms package [46,47], in which the dependent variables are the level of noise exposure, the level of NO 2 exposure and the inhaled dose of NO 2 , and the observations are the one-minute segments (N = 4,157, 4,368 and 4,368, respectively). The models proposed here are largely based on recent studies [43,48,49]: GAMMAR models (generalized additive mixed model with an autoregressive term) with a student distribution for the dependent variable [50]. Consequently, four types of terms were introduced into each model: random effects terms, non-linear terms (i.e.…”

Section: Modelling Road Traffic Noise Exposure Air Pollution Exposure and Inhalationmentioning

confidence: 99%

“…As done previously [43,48,49], to take the temporal and spatial variability into account, the time of day (number of minutes passed since 08:00) and the geographic coordinates were introduced as non-linear terms (i.e., splines). Therefore, we expected to observe peaks of exposure and inhalation during the morning and evening rush hours, and in the most densely populated areas of Delhi.…”

Section: Modelling Road Traffic Noise Exposure Air Pollution Exposure and Inhalationmentioning

confidence: 99%

Cycling in one of the most polluted cities in the world: Exposure to noise and air pollution and potential adverse health impacts in Delhi

2021

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Background In India, many cities struggle with extreme levels of air pollution and noise. Delhi, in particular, has the notorious reputation of being one of the most polluted cities in the world. Cyclists constitute a particularly exposed population, since they cycle among motor vehicles without any protection. This paper modeled the cyclists’ exposure to nitrogen dioxide (NO2) and noise in Delhi, India. Methods Using primary data collected on 1,229 kms of roads in Delhi, Generalized Additive Mixed Models with Auto-Regressive terms (GAMMAR) are constructed for noise exposure, NO2 exposure and NO2 inhalation doses. Results Results show that cyclists are exposed to 47 µg/m3 of NO2 and 3.3 dB(A) more when cycling on a primary road than on a residential street. Using WHO guideline values for noise and air pollution, we assessed how many minutes of inhaling doses and noise doses become potentially harmful to cyclists’ health in Delhi. Such thresholds are quickly exceeded: after cycling one hour in an area with moderate predicted values of noise and air pollution, the noise dose and inhaled dose of NO2 will reach 212% and 403 µg on residential streets, and 459% and 482 µg on primary roads, respectively. Conclusion Policy makers should take these results into account to minimize cyclists’ exposure, especially for the most deprived people.

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Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris

Cited by 13 publications

References 62 publications

Cyclists’ exposure to atmospheric and noise pollution: a systematic literature review

Cyclists’ exposure to atmospheric and noise pollution: a systematic literature review

Sources and Applications of Emerging Active Travel Data: A Review of the Literature

Cycling in one of the most polluted cities in the world: Exposure to noise and air pollution and potential adverse health impacts in Delhi

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