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Different acellular assays were developed to measure particulate matter’s (PM) oxidative potential (OP), a metric used to predict the ability of PM in generating oxidative stress in living organisms. However, there are still fundamental open issues regarding the complex redox equilibria among the involved species which could include reducing compounds. The aim of this study was the pilot application of the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay to PM in order to evaluate the presence of reducing species. The assay, commonly applied to biological matrices, was adapted to PM and showed good analytical performances. It allowed the analysis of conventional 24 h airborne PM samples with suitable sensitivity and good repeatability of the measurements. The assay was applied to seven samples representing possible PM contributes (certified urban dust NIST1648a; brake dust; Saharan dust; coke dust; calcitic soil dust; incinerator dust; and diesel particulate matter certified material NIST1650b) and to PM2.5 field filters. The same samples were also analyzed for elements. Preliminary results indicated that the assay gave a linear response and that detectable amounts of reducing species were present in PM samples. The combined application of DPPH and conventional OP assays could then permit, in the future, to gain more knowledge about the reaction and/or competition between oxidative and reducing processes.

The RHAPS (Redox-Activity And Health-Effects Of Atmospheric Primary And Secondary Aerosol) project was launched in 2019 with the major objective of identifying specific properties of the fine atmospheric aerosol from combustion sources that are responsible for toxicological effects and can be used as new metrics for health-related outdoor pollution studies. In this paper, we present the overall methodology of RHAPS and introduce the phenomenology and the first data observed. A comprehensive physico-chemical aerosol characterization has been achieved by means of high-time resolution measurements (e.g., number size distributions, refractory chemical components, elemental composition) and low-time resolution analyses (e.g., oxidative potential, toxicological assays, chemical composition). Preliminary results indicate that, at the real atmospheric conditions observed (i.e., daily PM1 from less than 4 to more than 50 μg m−3), high/low mass concentrations of PM1, as well as black carbon (BC) and water soluble Oxidative Potential (WSOP,) do not necessarily translate into high/low toxicity. Notably, these findings were observed during a variety of atmospheric conditions and aerosol properties and with different toxicological assessments. Findings suggest a higher complexity in the relations observed between atmospheric aerosol and toxicological endpoints that go beyond the currently used PM1 metrics. Finally, we provide an outlook to companion papers where data will be analyzed in more detail, with the focus on source apportionment of PM1 and the role of source emissions on aerosol toxicity, the OP as a predictive variable for PM1 toxicity, and the related role of SOA possessing redox-active capacity, exposure-response relationships for PM1, and air quality models to forecast PM1 toxicity.

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Water-soluble and insoluble fractions of airborne particulate matter (PM) exhibit different toxicological potentials and peculiar mechanisms of action in biological systems. However, most of the research on the oxidative potential (OP) of PM is focused exclusively on its water-soluble fraction, since experimental criticisms were encountered for detaching the whole PM (soluble and insoluble species) from field filters. However, to estimate the actual potential effects of PM on human health, it is essential to assess the OP of both its water-soluble and insoluble fractions. In this study, to estimate the total OP (TOP), an efficient method for the detachment of intact PM10 from field filters by using an electrical toothbrush was applied to 20 PM10 filters in order to obtain PM10 water suspensions to be used for the DCFH, AA and DTT oxidative potential assays (OPDCFH, OPAA and OPDTT). The contribution of the insoluble PM10 to the TOP was evaluated by comparing the TOP values to those obtained by applying the three OP assays to the water-soluble fraction of 20 equivalent PM10 filters. The OP of the insoluble fraction (IOP) was calculated as the difference between the TOP and the WSOP. Moreover, each PM10 sample was analyzed for the water-soluble and insoluble fractions of 10 elements (Al, Cr, Cs, Cu, Fe, Li, Ni, Rb, Sb, Sn) identified as primary elemental tracers of the main emission sources in the study area. A principal component analysis (PCA) was performed on the data obtained to identify the predominant sources for the determination of TOP, WSOP, and IOP. Results showed that water-soluble PM10 released by traffic, steel plant, and biomass burning is mainly responsible for the generation of the TOP as well as of the WSOP. This evidence gave strength to the reliability of the results from OP assays performed only on the water-soluble fraction of PM. Lastly, the IOPDCFH and IOPDTT were found to be principally determined by insoluble PM10 from mineral dust.

Bees and their products are useful bioindicators of anthropogenic activities and could overcome the deficiencies of air quality networks. Among the environmental contaminants, mercury (Hg) is a toxic metal that can accumulate in living organisms. The first aim of this study was to develop a simple analytical method to determine Hg in small mass samples of bees and beehive products by cold vapor atomic fluorescence spectrometry. The proposed method was optimized for about 0.02 g bee, pollen, propolis, and royal jelly, 0.05 g beeswax and honey, or 0.1 g honeydew with 0.5 mL HCl, 0.2 mL HNO3, and 0.1 mL H2O2 in a water bath (95 °C, 30 min); samples were made up to a final volume of 5 mL deionized water. The method limits sample manipulation and the reagent mixture volume used. Detection limits were lower than 3 µg kg−1 for a sample mass of 0.02 g, and recoveries and precision were within 20% of the expected value and less than 10%, respectively, for many matrices. The second aim of the present study was to evaluate the proposed method’s performances on real samples collected in six areas of the Lazio region in Italy.