Despite the progress made in recent years, reliable modeling of indoor air quality is still far from being obtained. This requires better chemical characterization of the pollutants and airflow physics included in forecasting tools, for which field observations conducted simultaneously indoors and outdoors are essential. The project “Integrated Evaluation of Indoor Particulate Exposure” (VIEPI) aimed at evaluating indoor air quality and exposure to particulate matter (PM) of humans in workplaces. VIEPI ran from February 2016 to December 2019 and included both numerical simulations and field campaigns carried out in universities and research environments located in urban and non-urban sites in the metropolitan area of Rome (Italy). VIEPI focused on the role played by micrometeorology and indoor airflow characteristics in determining indoor PM concentration. Short- and long-term study periods captured diurnal, weekly, and seasonal variability of airflow and PM concentration. Chemical characterization of PM₁₀, including the determination of elements, ions, elemental carbon, organic carbon, and bioaerosol, was also carried out. Large differences in the composition of PM₁₀ were detected between inside and outside as well as between different periods of the day and year. Indoor PM composition was related to the presence of people, to the season, and to the ventilation regime.

Due to its importance in airborne disease transmission, especially because of the COVID-19 pandemic, much attention has recently been devoted by the scientific community to the analysis of dispersion of particle-laden air clouds ejected by humans during different respiratory activities. In spite of that, a lack of knowledge is still present particularly with regard to the velocity of the emitted particles, which could differ considerably from that of the air phase. The velocity of the particles is also expected to vary with their size. In this work, simultaneous measurements of size and velocity of particles emitted by humans while speaking have been performed by means of Interferometric Laser Imaging Droplet Sizing (ILIDS). This technique allowed us to detect emitted particles with size down to 2 µm as well as to quantify all three components of the velocity vector and the particle concentration. The outcomes of this work may be used as boundary conditions for numerical simulations of infected respiratory cloud transmission. Graphical abstract

The parametrizations of meteorological variables provided by the Monin–Obukhov similarity theory (MOST) is of major importance for pollutant dispersion assessment. However, the complex flow pattern that characterizes the urban areas limits the applicability of the MOST. In this work, the performance of different existing parametrizations of the standard deviation of vertical wind velocity were tested in the city of Rome. Results were compared with experimental data acquired by a sonic detection and ranging (SODAR) and a sonic anemometer. Different scaling variables estimated from the anemometer data by considering two coordinate systems—one aligned with the geodetic reference frame and the other following the flow streamlines—were used to evaluate the effects of flow distortion due to the presence of buildings. Results suggest that the MOST parametrizations perform better if the scaling variables obtained using the coordinate system following the flow streamlines are used. This estimation of the scaling variables would make it possible to overcome the difficulties in conducting measurements of turbulent fluxes, either at different altitudes or even in the constant flux layer.