This work is an overview of the oxidative potential (OP) values up to date measured in Italy, with the aim to provide a picture of the spatial and seasonal variability of OP in the various geographical areas across Italy. The summarized works used the common acellular assays-based dithiothreitol (OP DTT ), ascorbic acid (OP AA ), glutathione (OP GSH ), and 2 ,7 -dichlorodfluorescein (OP DCFH ) assays. The paper describes the association of OP responses with PM chemical composition, the sensitivity of various acellular OP assays to PM components and emission sources, and PM size distribution of the measured OP values. Our synthesis indicates that crustal and transition metals (e.g., Fe, Ni, Cu, Cr, Mn, Zn, and V), secondary ions and carbonaceous components (elemental carbon, EC, organic carbon, OC and water soluble carbon, WSOC) show significant correlations with OP across different urban and rural areas and size ranges. These chemical species are mainly associated with various PM sources, including residual/fuel oil combustion, traffic emissions, and secondary organic aerosol formation. Although the OP assays are sensitive to the same redox-active species, they differ in the association with PM chemical components. The DDT assay is mainly sensitive to the organic compounds that are mostly accumulated in the fine PM fraction, i.e., tracers of burning sources, and redox active organics associated with other markers of photochemical aging. In contrast, OP AA and OP GSH were mostly responsive to metals, mainly those related to non-exhaust traffic emissions (Cu, Zn, Cr, Fe, Ni, Mn, Sn, Cd, Pb), that are mainly accumulated in the coarse PM. Among the investigated sites, our synthesis shows larger OP values in Trentino region and the Po Valley, that may be explained by the high density of anthropogenic sources, and the orographic and meteorological characteristics, that favor the pollutants accumulation and aerosol photo-oxidative aging. ). The acellular version of the 2 ,7 -dichlorodfluorescein (DCFH) assay uses the enzymatic production of the fluorescent probe largely used for the evaluation of oxidative stress in living cells.The present work summarizes the PM oxidative properties up to date measured in Italy using OP acellular assays, with the aim of giving a general insight of PM OP across the Italian territory, that has not been reported yet, in spite of the increasing number of OP measurements carried out in Europe [6,[19][20][21][22]. In addition, the study reviews the association described in previous studies between OP from different assays with several inorganic ad organic components, that effect PM oxidative properties, i.e., metals, ions, and carbonaceous components. The aim is to give a picture of the spatial and seasonal variability of different contributions to OP in the various geographical areas across Italy. The relevance of such an investigation is based on the large variability in the chemical composition of different PM size fractions in various locations across Italy, as a consequence of the stron...

This article describes the on-site monitoring of indoor air quality (IAQ) in school classrooms and laboratories. The students were personally involved in the monitoring experience, by using low-cost IAQ sensors, and then in evaluation and interpretation of the measured values. The joint school–university project, which provides lessons, equipment, and support to high school classes, is a model of how to engage students in real-world science research and learning. The obtained results pointed out two alerts: unacceptable high levels of fine particle matter (PM2.5)mainly entered into indoor environments from highly polluted outdoor airand uncomfortably high CO2 levelsdue to classroom crowding and inadequate ventilation.

Abstract. Primary biological aerosol particles (PBAPs) play an important role in the interaction between biosphere, atmosphere, and climate, affecting cloud and precipitation formation processes. The presence of pollen, plant fragments, spores, bacteria, algae, and viruses in PBAPs is well known. In order to explore the complex interrelationships between airborne and particulate chemical tracers (amino acids, saccharides), gene copy numbers (16S and 18S for bacteria and fungi, respectively), gas phase chemistry, and the particle size distribution, 84 size-segregated aerosol samples from four particle size fractions (< 1.0, 1.0–2.5, 2.5–10, and > 10 µm) were collected at the SMEAR II station, Finland, in autumn 2017. The gene copy numbers and size distributions of bacteria, Pseudomonas, and fungi in biogenic aerosols were determined by DNA extraction and amplification. In addition, free amino acids (19) and saccharides (8) were analysed in aerosol samples by hydrophilic interaction liquid chromatography–mass spectrometry (HILIC-MS). Different machine learning (ML) approaches, such as cluster analysis, discriminant analysis, neural network analysis, and multiple linear regression (MLR), were used for the clarification of several aspects related to the composition of biogenic aerosols. Clear variations in composition as a function of the particle size were observed. In most cases, the highest concentration values and gene copy numbers (in the case of microbes) were observed for 2.5–10 µm particles, followed by > 10, 1–2.5, and < 1.0 µm particles. In addition, different variables related to the air and soil temperature, the UV radiation, and the amount of water in the soil affected the composition of biogenic aerosols. In terms of interpreting the results, MLR provided the greatest improvement over classical statistical approaches such as Pearson correlation among the ML approaches considered. In all cases, the explained variance was over 91 %. The great variability of the samples hindered the clarification of common patterns when evaluating the relation between the presence of microbes and the chemical composition of biogenic aerosols. Finally, positive correlations were observed between gas-phase VOCs (such as acetone, toluene, methanol, and 2-methyl-3-buten-2-ol) and the gene copy numbers of microbes in biogenic aerosols.

Abstract. Primary biological aerosol particles (PBAPs) play an important role in the interaction between biosphere, atmosphere and climate, affecting cloud and precipitation formation processes. The contribution of pollen, plant fragments, spores, bacteria, algae and viruses to PBAPs is well known. In order to explore the complex interrelationships between airborne and particulate chemical traces (amino acids, saccharides), gene copy numbers, gas phase chemistry and the particle size distribution, 84 size-segregated aerosol samples from four particle size fractions ( 10 µm) were collected at SMEAR II station, Finland in autumn 2017. The gene copy numbers and size distribution of bacteria, Pseudomonas and fungi in PBAPs were determined by DNA extraction and amplification. In addition, free amino acids (19) and saccharides (8) were analyzed in aerosol samples by hydrophilic interaction liquid chromatography -mass spectrometry (HILIC-MS). Different machine learning (ML) approaches, such as cluster analysis, discriminant analysis, neural network and multiple linear regression (MLR) were used for the clarification of several aspects related to the PBAPs composition. Clear variations were observed for the composition of PBAPs as a function of the particle size. In most cases, the highest concentration values, gene copy numbers in the case of microbes, were observed for 2.5–10 µm particles followed by > 10 µm, 1–2.5 µm and

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