The Sniffer Bike project

Sniffer Bike was started in May 2019 in the Province of Utrecht, Netherlands. The bicycle sensor based project has a strong focus on the active involvement of cycling citizens and citizen science approaches to make new cycling data available. Sniffer Bike or Snuffelfiets is characterized by the active involvement of citizens in the form of collecting and exchanging bicycle sensor data. Benefits of projects as Sniffer Bike are that these can help to pinpoint local problems better, create more understanding of the current needs, and better predict future mobility behavior [1]. Moreover, actively involving citizens results in raising awareness amongst citizens, can initiate (or improve) the dialogue on the subject, and increase the exchange of data [2]. In addition to the GPS positions, the acceleration and the speed level, the sensor configuration on the 550 produced Sniffer Bike sensors are recording a large amount of environmentally relevant data (including fine particles PM2.5, temperature, humidity). A strong focus on air quality measurements can be perceived. The raw data is published on a daily basis on the Dutch website (

Utrecht, a historical city centrally located in the Netherlands close to Amsterdam, is famous for giving space to cyclists and pedestrians. Although space is limited, Utrecht has created one of the best bicycle infrastructures not only in Europe but even compared to other places in the Netherlands in terms of consistency, directness, attractiveness, safety, comfort, spatial integration, experience and social economic value. In 2014, more than 44 percent of the population were cycling [3]. The motivation of the Province of Utrecht to start the Sniffer Bike project is to stay one of the most competitive regions in Europe. The development to a healthier region with optimal living and working climate is an important part of this long term perspective. The Sniffer Bike project is an attempt to learn more about the air quality as well as the cycling behavior. The general public participates in this process by the data distribution. The interaction and communication with the society is improved. The data is also being used by the Province of Utrecht for the analysis of route choice and delays at traffic lights.

The city of Zwolle which is the capital of the Province of Overijssel and is located close to the Ijsselmeer, is also part of the Sniffer Bike project. Zwolle is seeking for information on the particulate matter levels, durations, speed and delays during bike trips to optimize future policies on bicycle mobility. In this context, the Sniffer Bike data gives new input to increase comfort, speed and safety for cyclists. Sniffer Bike in Zwolle is part of an ambitious mobility plan to raise the amount of bicycle trips by 20% in the next ten years. Before the implementation of Sniffer Bike, the municipality of Zwolle used different methods to gain insights in bike use and air quality levels. Bicycle use is measured in two ways. The first one is ODiN & OViN, a national research from CBS (‘central office of statistical analysis’) based on surveys (e.g. questions about transport motives at a particular day). The second one is the bicycle count week (Fietstelweek) which counts bicycle use for one week in the whole Netherlands. Air quality is measured by the NSL monitor tool (Nationaal Samenwerkingsprogramma Luchtkwaliteit, National Air Quality Cooperation Program, Once a year, this tool measures the air quality (PM10, PM2.5 and CO2), based on parameters as traffic or buildings. The outcome gives an accurate estimate for air quality levels. In the municipality of Zwolle the air quality will be measured by the NSL tool at least until the end of 2021.

Sensor technology

Sniffer Bike is based on the so called Particulate Matter Sensor SPS30 by Sensirion ( The MCERTS-certified SPS30 particulate matter (PM) sensor is applying laser scattering to determine the size and amount of the fine particles in the air. The manufacturer promises a lifetime of the sensor which is presented in Fig. 1 of more than ten years. Particulate matter with particle diameter up to 2.5 microns (PM2.5) belongs to the most dangerous air pollutants.

Fig. 1. Sensor unit used in the Sniffer Bike project.
Source: Province of Utrecht

Because of its small size, PM2.5 particles can move up deeply into the lungs what can lead to many health issues as asthma [4], cardiovascular disease [5] or autism [6]. The sensors are standardized attached between the bicycle handle and central bar. The data is transmitted in near real time via the mobile phone network. The more than 550 sensors are supplied to the citizens at various locations in the Netherlands (including Utrecht, Zwolle, ‘s-Hertogenbosch, Zeeland) and even in other European countries (e.g. in Denmark, Sweden). Further studies tested the feasibility of the air quality measurement based on mobile bike sensors. Bertero et al. [7] conducted successfully a study with state-of –the-art sensors to detect NO2 concentrations in the city of Marseille, France, with a small fleet of less than hundred bicycles. Low cost sensors can lead to uncertainties in terms of data quality [7]. Shen et al. [8] presented a study based on a sensor detecting particles, temperature, humidity including SD-card, GPS-receiver and a NB-IoT communication module. The PM2.5/PM10 laser sensor which was tested in a Chinese bike sharing system can obtain 0.3-10 µ suspended particulate matter concentration in the air and, according to the authors, delivers data of high quality [8].

Citizen participation

According to the Province of Utrecht demographic information about the participants was not recorded in detail because of privacy concerns and the focus on other aspects of the data. But a high motivation for elderly people to participate was perceived. Many middle and higher aged cyclists were involved in exchange formats or have contacted the project by email. Many less tech-savvy people showed interest to be an active part of the project. Sniffer Bike offers a good example of how the bike trips of the cyclists can be made freely available for the general public as open bicycle data over a longer period of time. On the one hand, the anonymized raw data of the most recent bicycle trips is published weekly in a Dutch open data portal.  On the other hand, the current routes, including information on air quality, are visualized on a daily basis on a publicly accessible interactive dashboard ( On a personalized website with individual log-in the participants may find their personal bicycle trips and relating statistics.

The data collection in the Province started in May 2019 and was supposed to run until the start of Vuelta a España[1] in Utrecht in August 2020 [9]. Because of the Corona crisis the event was cancelled and the data collection period was extended until the end of January 2021. About 500 volunteers in the Province of Utrecht and fifty volunteers in the neighboring Province of Gelderland attached the device on their bicycles to collect environmental and bicycle data. In order to validate the sensor data, RIVM (Rijksinstituut voor Volksgezondheid en Milieu, Netherlands National Institute for Public Health and the Environment) developed a validation process based on co-located Sensirion SPSP30s at three (static) national air quality measurement network sites. The Sniffer Bike project has been evaluated and at the 23rd of January 2021 during an online event the Province of Utrecht announced that the community based approach will be continued as part of a community based Citizen Science programme [10]. This is contrary to the Province of Gelderland. The key difference between the two provinces is the number of volunteers and the amount of data generated. It can be concluded that it is essential to have a critical mass to reach relevant results.

As part of the BITS project the sensor devices have also been deployed in the city of Zwolle which published a call for participation with special focus on frequent bicycle users. The bike sensors became a part of the Senshagen project ( that focused on obtaining insight in climate and participating with the citizens of the neighbourhood of Stadhagen by collecting sensor data. The citizens of Zwolle showed high interest in participating in the Sniffer Bike initiative. The project has started at the 4th December 2019 with a participants evening where the sensors were handed out to the participants. Ten regular cyclists between 25 and 55 years adopted a sensor on their bike and started making measurements with every trip they make. The motivation of the city administration to be part of the project is to gather new information about particulate matter levels, length of trips, speed during the trips and delays on routes. For the initial goal to obtain more insight in air quality on frequently used bike lanes, there are more bike sensors needed to draw conclusions. In contrast to the Province of Gelderland, the city of Zwolle is planning to scale up the Sniffer Bike project 2021 as part of the BITS initiative. The goal is to supply between 100 and 250 sensors to interested cyclists in and around Zwolle to different target groups as bike couriers, company bikes, members of the local cyclist federation or school pupils.

[1] It is intended to reorganize the event in Utrecht in 2022. Utrecht will be then the first city in the world that have hosted all three major cycling races (beyond the Giro d’Italia 2010 and the Torur de France in 2010). The trip at the Vuelta a España should be a ride about 24 kimometres, starting from Jaarbeurs trade and conference venues crossing through working class districts, the suburbs, the shopping centre and the University. The cyclists will enter the Province at Rhenen and are crossing the Heuvelrug National Park. See Hitman and Hanenbergh, pp. 74 and 124.

Results of the data analysis (Sniffer Bike)

As part of the EU project BITS, the business informatics department VLBA of the University of Oldenburg prepared and evaluated the data records of the Sniffer Bike project. During the first 10 months of the project, more than 100.000 data points in the Netherlands were recorded. About 62.336 trips with an average distance of around 7 kilometers and an average duration of 35:45 minutes per trip with an average speed level of 13.79 km/h were measured in the regions of Utrecht and Zwolle between May 2019 and the end of March 2021. Fig. 2 shows a heatmap of the bicycle trips in the Netherlands.

Fig. 2. Heatmap of bicycle trips in the Netherlands (ArcGis, copyright by Esri)

All Sniffer Bike trips were visualized according to the starting time of the bicycle trips (time stamp). The visualization in Fig. 3 shows clear peaks in the morning and the afternoon.

Fig 3. Hourly values (Sniffer Bike, MS Power BI).

A high share of bicycle trips when commuting to work or school can be assumed. It can be concluded that the bicycle is strongly used in daily life in the Netherlands. It has to be mentioned at this point that the Corona virus has changed cycling behavior: It seems to be that recreational bicycle use has increased a lot during that time. Fig. 4 shows the starting times of the bicycle trips (time stamp) between March and June 2020.

Fig 4. Hourly values spring 2020 (Snifferbike, MS Power BI)

The morning peak is much less remarkable instead of a peak that durates the whole afternoon from three to six pm. It can be concluded that the bicycle is more used during leisure time in the Netherlands than before. This is also proven by a look to the average distances and durations (Fig. 5) that show a remarkable increase in spring 2020. The citizens stayed at home for home office or schooling and used their bicycles more during leisure time compared to commuting to the working or education place.

Although the behavior of the cyclists has changed, according to other publications, the total bicycle use in the Netherlands remained stable during the Corona crisis [11].

Fig 5. Average distances and durations of bicycle trips in the Netherlands (MS Power BI)

Part of the Sniffer Bike data analysis was also the observation of the weather influence on cycling behavior, namely distances, durations and speed levels. Under dry weather conditions (moderate) the average distance of a Sniffer Bike trip in the Province of Utrecht is about 7.24 km long and has a duration of about 37.5 minutes. If the weather conditions are bad when a trip starts the average distance shortens. This is the case for the classifications cold (6.5 km in 30 minutes), windy (6.8 km in 32 min.) or light rain (6.5 km in 33 min.). Surprisingly, under snowy weather conditions the distances are increasing (heavy snow 8.1 km in in 36 minutes). Bad weather conditions have an impact on distances but not on speed levels which lies between 13 and 14 km/h. The only exception are the snow classifications (heavy snow 15.7 km/h, light snow 16 km/h) what could be an outlier because of the limited number of trips (179). As Tab. 1 shows, there seems to be no correlation between the speed levels and differing weather conditions.

Because the Sniffer Bike sensor is gathering only one measurement in around 11 seconds it was not possible to conduct very specific data analysis regarding the state of the infrastructure (vibrations) or the brakings of the cyclists. What brings a huge benefit of the project is the fact that the Sniffer Bike sensor allows an oberservation of the air quality. Intersections can be interpreted as problem points which tend to have a highly increased concentration of PM2.5 particles. In general, main roads show a much more problematic air quality compared to less frequented roads nearby. Industrious zones (e.g. Hanzeland in Zwolle) also show increased concentration of fine particles in the air what is visualized in Fig. 6. 

Fig 6. Heatmap of fine particles in Zwolle (ArcGis, copyright by Esri)


  1. Booth, C.; Richardson, T. (2001). Placing the public in integrated transport planning. Transport Policy, pp. 141-149.  
  2. Kobernus, M; Berre, A.J.; Rombouts, R.; Fredriksen, M; Liu, H.Y.; Gonzalez, M; Bartonova, A. (2013). A Practical Approach to an Integrated Citizens Observatory: The CITI-Sense Framework.  In: Environmental Information Systems and Services – Infrastructures and Platforms 2013 – with Citizens Observatories, Linked Open Data and SEIS/SDI Best Practices. Neusiedl am See:
  3. Hull, A. and O’Holleran, C. (2014). Bicycle infrastructure: can good design encourage cycling? In: Urban, Planning and Transport Research, 2:1, pp. 369-406.
  4. Thompson, E. J. (2018). Airborne Particulate Matter: Human Exposure and Health Effects. In: Journal of Occupational and Environmental Medicine, Vol.60(5), pp.392-423.
  5. Pope, C.A.; Cohen, A.J.; Burnett, R.T. (2018). Cardiovascular Disease and Fine Particulate Matter: Lessons and Limitations of an Integrated Exposure–Response Approach. In: Circulation Research, Vol.122(12), pp.1645-1647.
  6. Volk, H.E.; Lurmannm F.; Penfold, B.; Hertz-Piciotto, I.; McConnell, R. (2013). Traffic-Related Air Pollution, Particulate Matter, and Autism. In: JAMA Psychiatry. 70(1), pp.71-77.
  7. Bertero, C.; Léon, J.F.; Trédan, G.; Roy, M.; Armengaud, A. (2020). Urban-Scale NO2 Prediction with Sensors Aboard Bicycles: A Comparison of Statistical Methods Using Synthetic Observations. Atmosphere 2020, 11, 1014, pp. 1-16.
  8. Shen, S.; Lv, C.; Xu, X.; Liu, X. (2019). A Bicycle-Borne Sensor Node for Monitoring Air Pollution Based on NB-IoT. X. B. Zhai et al. (Eds.): MLICOM 2019, LNICST 294, pp. 325–332. Cham: Springer Nature Switzerland.
  9. Hitman, L.; Hanenbergh, K. (2020). Fietsen Maken Utrecht: Utrecht is Cycling. Utrecht/Antwerp: Kosmos Uitgevers.
  10. de Haas, M.; Hamersma, M. (2020). Fietsfeiten: nieuwe inzichten. Den Haag, Ministerie van Infrastructuur en Waterstaat, Kennisinstituut voor Mobiliteitsbeleid (KiM).
  11. Schouwenaar, C. (2021). Snuffelfiets: fietsend meten met sensoren. Published in January 2021. Last Access 8th of February 2021.