Air pollution measurements during commuting in Lyon

Air pollution is a dramatic issue that grips the majority of densely populated cities in the world. It is nowadays quite evident that there is a relationship between air quality and some types of cancers (i.e. lung and bladder cancer), as reported by the International Agency for Research on Cancer (IARC 2012). Although the time spent commuting usually represents a small portion of a person's daily time (3-6%), it is responsible around for 21% of daily personal exposure and roughly 30% of the total inhaled dose (Dons et al. 2012). To gain information on this topic, we conducted an air quality measurement campaign (six weeks between November and December 2021) on three different routes within the metropolitan city of Lyon (France). These routes were chosen to be representative of different urban areas (e.g. city centre, periphery, vegetated areas). The measurements were taken two times for day (i.e. in the morning and the evening, in order to simulate the commuters round trip) using four different modes (walk, bike, car and public transport). Two different portable air quality sensors were used to measure the pollutants: the MONICA sensors (developed by ENEA, De Vito et al. 2021) that measure PM1, PM2.5, PM10, NO2, CO and O3 and the AirBeam 2 sensors (provided by ATMO AURA) that measure only the particular matters. The objective of this study is twofold: from one side to assess the exposure choosing different modes of commuting and, from the other side, to evaluate how the influence of the meteorological-climatic variables (e.i. temperature, relative humidity, precipitation, wind direction, wind speed, cloud cover, solar radiation and atmospheric boundary layer stability/instability) affect the air quality. Preliminary results show that private car users are generally affected by lower levels of air pollution with respect to the other modes (as expected, Okokon et al. 2017), but this is strongly influenced by the type of ventilation used (internal or external air recirculation, open and closed windows). ReferenceDe Vito, S., Esposito, E., Massera, E., Formisano, F., Fattoruso, G., Ferlito, S., ... & Di Francia, G. (2021). Crowdsensing IoT Architecture for Pervasive Air Quality and Exposome Monitoring: Design, Development, Calibration, and Long-Term Validation. Sensors, 21(15), 5219.Dons, E., Panis, L. I., Van Poppel, M., Theunis, J., & Wets, G. (2012). Personal exposure to black carbon in transport microenvironments. Atmospheric Environment, 55, 392-398.IARC Working Group on the Evaluation of Carcinogenic Risks to Humans. (2012). Chemical agents and related occupations. IARC monographs on the evaluation of carcinogenic risks to humans, 100, 9–562.Okokon, E. O., Yli-Tuomi, T., Turunen, A. W., Taimisto, P., Pennanen, A., Vouitsis, I., ... & Lanki, T. (2017). Particulates and noise exposure during bicycle, bus and car commuting: A study in three European cities. Environmental Research, 154, 181-189.