Mario Lovrić, Valentino Petrić, Dejan Strbad, Teo Terzić, Sanja Frka, Ana Cvitešić Kušan, Jose Fermoso, Sebastian Düsing, Honey Dawn Alas, Mila Dobrić Ladavac, Ivan Bilić, Marko Batrac, Simonas Kecorius, Gordana Pehnec, Tajana Horvat, Ivana Jakovljević, Nikolina Račić, Ivan Bešlić, Darijo Brzoja, Vesna Gugec, Maria Figols, Xabier Aláez, Hana Matanović, Anđelko Žigman, Michael Forsmann, Anneli Toomis, Jürgo-Sören Preden, Alessandro Battaglia, Ivano Battaglia, Gianna Karanasiou, Frederik Weis, Jon Switters, Francesco Mureddu
- Indoor air quality (IAQ) significantly influences human health, as individuals spend up to 90% of their time indoors, where air pollutants can accumulate and interact dynamically. Despite advancements in monitoring technology, challenges remain in capturing the temporal and spatial variability of pollutants and understanding the interaction between indoor and outdoor environments. This study addresses these gaps by introducing a comprehensive dataset from a controlled experimental room in Croatia, leveraging a multi-instrumental approach to monitor IAQ across various real-life scenarios. The dataset integrates measurements from low-cost sensors, reference-grade devices, and auxiliary systems to track pollutants such as particulate matter (PM), black carbon (BC), volatile organic compounds (VOC), and indoor events deemed relevant for the assessment of pollutant levels. Key experiments simulated household activities, including cooking, cleaning, human presence, and ventilation, capturingIndoor air quality (IAQ) significantly influences human health, as individuals spend up to 90% of their time indoors, where air pollutants can accumulate and interact dynamically. Despite advancements in monitoring technology, challenges remain in capturing the temporal and spatial variability of pollutants and understanding the interaction between indoor and outdoor environments. This study addresses these gaps by introducing a comprehensive dataset from a controlled experimental room in Croatia, leveraging a multi-instrumental approach to monitor IAQ across various real-life scenarios. The dataset integrates measurements from low-cost sensors, reference-grade devices, and auxiliary systems to track pollutants such as particulate matter (PM), black carbon (BC), volatile organic compounds (VOC), and indoor events deemed relevant for the assessment of pollutant levels. Key experiments simulated household activities, including cooking, cleaning, human presence, and ventilation, capturing their impacts on IAQ with high temporal resolution. The resulting dataset comprises over 19 subsets. This work contributes to the Horizon EDIAQI project, supporting the development of evidence-driven strategies to improve IAQ.…
