Abstract
Health effect estimates for PM2.5 commonly assume that human exposure is accurately represented by ambient concentrations. However, since people spend approximately 90% of their time indoors, with up to 70% of that time spent at home, relying solely on ambient concentrations introduces biases in health effect estimates. Overcoming this issue requires state-of-the-art exposure modeling that considers indoor infiltration of ambient pollutants using specific infiltration factors (IFs). However, reliable data on IFs are often lacking, and the impact of applied IFs on exposure estimates remains poorly understood.
To address this gap, we conducted a combined measurement-modeling study in residential environments in Athens, Greece, as part of the H2020 ATMO ACCESS project PIRAthe (Particulates Infiltrating Residencies in Athens):
1. We conducted a field campaign to measure indoor and outdoor concentrations of PM2.5 (PupleAir PA-II, Antilope mini stations) and black carbon (Aethlabs MA200) at various residential locations within the Greater Athens Area.
2. We derived IFs and analyzed them in relation to climatic conditions and accompanying surveys that were distributed to all residents.
3. We applied these IFs in the dynamic urban exposure model UNDYNE (Ramacher et al. 2019, 2020), in conjunction with urban-scale air quality modeling results from the EPISODE-CityChem (Karl et al. 2019) Chemistry Transport Model.
Our findings revealed limited spatial variability in the derived IFs, which were primarily influenced by climatic conditions and residents' activities (such as ventilation or cooking). Applying these IFs in the dynamic exposure model led to significant changes in total and residential exposure estimates for PM2.5 compared to generic or IF-neglected scenarios.
Overall, our study underscores the importance of realistic IFs for accurate exposure assessment and demonstrates a state-of-the-art approach to estimating air pollution exposure. Such accurate assessments are vital for implementing efficient actions to reduce air pollution, population exposure, and consequently, adverse health effects.
