Air Quality Sensors Systems as Tools to Support Guidance in Athletics Stadia for Elite and Recreational Athletes

Mar Viana, Kostas Karatzas, Athanasios Arvanitis, Cristina Reche, Miguel Escribano, Edurne Ibarrola-Ulzurrun, Paolo Emilio Adami, Fréderic Garrandes and Stéphane Bermon
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Mar Viana: Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034 Barcelona, Spain
Kostas Karatzas: Environmental Informatics Research Group, School of Mechanical Engineering, Aristotle University, 54124 Thessaloniki, Greece
Athanasios Arvanitis: Environmental Informatics Research Group, School of Mechanical Engineering, Aristotle University, 54124 Thessaloniki, Greece
Cristina Reche: Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034 Barcelona, Spain
Miguel Escribano: Kunak Technologies, 31160 Orcoyen, Spain
Edurne Ibarrola-Ulzurrun: Kunak Technologies, 31160 Orcoyen, Spain
Paolo Emilio Adami: Health and Science Department, World Athletics, 98000 Monaco, Monaco
Fréderic Garrandes: Health and Science Department, World Athletics, 98000 Monaco, Monaco
Stéphane Bermon: Health and Science Department, World Athletics, 98000 Monaco, Monaco

IJERPH, 2022, vol. 19, issue 6, 1-18

Abstract: While athletes have high exposures to air pollutants due to their increased breathing rates, sport governing bodies have little guidance to support events scheduling or protect stadium users. A key limitation for this is the lack of hyper-local, high time-resolved air quality data representative of exposures in stadia. This work aimed to evaluate whether air quality sensors can describe ambient air quality in Athletics stadia. Sensing nodes were deployed in 6 stadia in major cities around the globe, monitoring NO 2 , O 3 , NO, PM 10 , PM 2.5 , PM 1 , CO, ambient temperature, and relative humidity. Results demonstrated that the interpretation of hourly pollutant patterns, in combination with self-organising maps (SOMs), enabled the interpretation of probable emission sources (e.g., vehicular traffic) and of atmospheric processes (e.g., local vs. regional O formation). The ratios between PM size fractions provided insights into potential emission sources (e.g., local dust re-suspension) which may help design mitigation strategies. The high resolution of the data facilitated identifying optimal periods of the day and year for scheduling athletic trainings and/or competitions. Provided that the necessary data quality checks are applied, sensors can support stadium operators in providing athlete communities with recommendations to minimise exposure and provide guidance for event scheduling.

Keywords: air pollution; competitions; exposure; stadiums; track and field; training; performance; exercise (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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