- 1Finnish Institute of Occupational Health, Helsinki, Finland (mikko.poikkimaki@ttl.fi)
- 2Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany
- 3VTT Technical Research Centre of Finland Ltd, Tampere, Finland
Industrial air pollutants pose safety and health risks to workers. This study aims to better understand the spatial and temporal distribution of air pollutants in industrial working environments. We developed and installed a novel low-cost sensor network in multiple workplaces: indoors at a steel factory, outdoors at a ferrochromium mill and on a cruise ship’s car deck. The stationary sensor networks are composed of multiple custom sensing nodes. Each node is equipped with low-cost sensors to assess gaseous components, particulate matter, temperature, and humidity. Air quality measurements using validated traditional occupational hygiene methods and high-end portable direct-reading instruments are performed stationary and mobile. Mobile devices carried by workers and unmanned aerial/ground vehicles complement the measurements by the stationary sensor network. The results consist of evaluations carried out by combining the sensor data, contextual information, and the results obtained with traditional exposure assessment methods. Can this data fusion be used to assess exposure and target risk management measures? Can real time sensor measurements support the worker safety? The short answer is YES!, but further steps are necessary to improve the sensor data reliability and applicability for detailed occupational exposure assessment. We present pollutant concentration maps and time series analysis, which are valuable for planning control measures and developing worker guidance to improve industrial safety. We further discuss the advantages and disadvantages of the available sensors for industrial air quality measurements and present the next steps of research needed for wider application of these safety technologies.
This research project, Robot-assisted Environmental Monitoring for Air Quality Assessment in Industrial Scenarios (RASEM), has received funding from the Finnish Work Environment Fund, Finnish Institute of Occupational Health, and Bundesanstalt für Materialforschung und –prüfung (BAM) under Saf€ra 2018 joint call: new technologies, new trends and monitoring safety performance.
How to cite: Poikkimäki, M., Kangas, A., Winkler, N. P., Neumann, P. P., Leikas, M., and Säämänen, A.: Can low-cost sensor networks help industrial air quality?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-42, https://doi.org/10.5194/egusphere-egu26-42, 2026.