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.

Exposure to ultrafine particles has been associated with short- and long-term effects on human health. The object of this paper was to assess Particle Number Concentration (PNC) and size distribution in a university environment and study the indoor/outdoor relationships. Measurements were carried out using co-located (indoor/outdoor) condensation particle counters and size spectrometers during two seasonal periods characterized by different meteorological conditions at five selected classrooms different for size, capacity, floor and use destination. PNC was dominated by particles in the ultrafine mode both indoor and outdoor. The indoor/outdoor ratios were on average between 1 and 1.2 in the summer and between 0.6 and 0.9 in the winter. Mostly the differences found among classrooms could be related to the condition of use (i.e., crowding, natural air exchange, air conditioning, seasonality). Only little differences were found among PNC measured immediately outside the classrooms. Based on information taken during the measurement campaigns, on the classrooms condition of use, it was possible to assess as a source of indoor particles in the coarse mode, the presence of students and teachers.

GAMs were implemented to evaluate the spatial variation in concentrations of 33 elements in PM₁₀, in their water-soluble and insoluble fractions used as tracers for different emission sources. Data were collected during monitoring campaigns (November 2016–February 2018) in the Terni basin (an urban and industrial hotspot of Central Italy), using an innovative experimental approach based on high-spatial-resolution (23 sites, approximately 1 km apart) monthly samplings and the chemical characterization of PM₁₀. For each element, a model was developed using monthly mean concentrations as the response variable. As covariates, the temporal predictors included meteorological parameters (temperature, relative humidity, wind speed and direction, irradiance, precipitation, planet boundary layer height), while the spatial predictors encompassed distances from major sources, road length, building heights, land use variables, imperviousness, and population. A stepwise procedure was followed to determine the model with the optimal set of covariates. A leave-one-out cross-validation method was used to estimate the prediction error. Statistical indicators (Adjusted R-Squared, RMSE, FAC2, FB) were used to evaluate the performance of the GAMs. The spatial distribution of the fitted values of PM₁₀ and its elemental components, weighted over all sampling periods, was mapped at a resolution of 100 m.

High-resolution measurements of ultrafine particle concentrations in ambient air are needed for the study of health human effects of long-term exposure. This work, carried out in the framework of the VIEPI project (Integrated Evaluation of Indoor Particulate Exposure), aims to extend current knowledge on small-scale spatio-temporal variability of Particle Number Concentration (PNC, considered a proxy of the ultrafine particles) at a local scale domain (1 km × 1 km). PNC measurements were made in the university district of San Lorenzo in Rome using portable condensation particle counters for 7 consecutive days at 21 sites in November 2017 and June 2018. Generalized Additive Models (GAMs) were performed in the area for winter, summer and the overall period. The log-transformed two-hour PNC averages constitute the response variable, and covariates were grouped by urban morphology, land use, traffic and meteorology. Winter PNC values were about twice the summer ones. PNC recorded in the university area were significantly lower than those observed in the external routes. GAMs showed a rather satisfactory result in order to capture the spatial variability, in accordance with those of other previous studies: variances were equal to 71.1, 79.7 and 84%, respectively, for winter, summer and the overall period.

Wildfires are relevant sources of PM emissions and can have an important impact on air pollution and human health. In this study, we examine the impact of wildfire PM emissions on the Piemonte (Italy) air quality regional monitoring network using a Generalized Additive Mixed Model. The model is implemented with daily PM₁₀ and PM_2.5 concentrations sampled for 8 consecutive years at each monitoring site as the response variable. Meteorological data retrieved from the ERA5 dataset and the observed burned area data stored in the Carabinieri Forest Service national database are used in the model as explanatory variables. Spline functions for predictive variables and smooths for multiple meteorological variables’ interactions improved the model performance and reduced uncertainty levels. The model estimates are in good agreement with the observed PM data: adjusted R² range was 0.63–0.80. GAMMs showed rather satisfactory results in order to capture the wildfires contribution: some severe PM pollution episodes in the study area due to wildfire air emissions caused peak daily levels up to 87.3 µg/m³ at the Vercelli PM₁₀ site (IT1533A) and up to 67.7 µg/m³ at the Settimo Torinese PM_2.5 site (IT1130A).

Addressing the planetary crisis associated with climate change, biodiversity loss, global pollution, and public health requires novel and holistic approaches. Here, we present the methodology and initial results of an experiment conducted in Rome within the framework of the National Biodiversity Future Center (NBFC) project, Spoke 6. The major objective of this study was to outline the planetary health approach as a lens to assess urban health. This transdisciplinary case study explored the relationship between urban traffic-related external exposome and pro-oxidative responses in humans and plants. This methodology is based on the integration of atmospheric dynamics modeling, state-of-the-art aerosol measurements, biomonitoring in human cohorts, in vitro cellular assays, and the assessment of functional trait markers in urban trees. The results indicate that short-term exposure to urban aerosols, even at low concentrations, triggers rapid oxidative and inflammatory responses in bronchial epithelial cells, modulates gene and miRNA expression, alters gut microbiota diversity, and induces functional trait changes in urban trees. This study also highlights the feedback mechanisms between vegetation and atmospheric conditions, emphasizing the role of urban greenery in modulating microclimate and exposure. The methodology and initial results presented here will be further analyzed in future studies to explore proof of a cause–effect relationship between short-term exposure to traffic-related environmental stressors in urban areas and oxidative stress in humans and plants, with implications for chronic responses. In a highly urbanized world, this evidence could be pivotal in motivating the widespread implementation of planetary health approaches for assessing urban health.