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Some studies suggested a role of the atmospheric particulate matter (PM) and of its oxidative potential (OP) in determining adverse health effects. Several works have focused on characterisation of source contributions to PM OP, mainly using three approaches: correlation between OP and chemical markers of specific sources; use of OP as input variable in source apportionment with receptor models; and multi-linear regression (MLR) between OP and source contributions to PM obtained from receptor models. Up to now, comparison of results obtained with different approaches on the same dataset is scarce. This work aims to perform a OP study of PM2.5 collected in an industrial site, located near a biogas production and combustion plant (in southern Italy), comparing different approaches to investigate the contributions of the different sources to OP. The PM2.5 samples were analysed for determining ions, metals, carbonaceous components, and OP activity with the DTT (dithiotreitol) assay. Results showed that OP normalised in volume (DTTV) is correlated with carbonaceous components and some ions (NO3−, and Ca2+) indicating that PM of combustion, secondary, and crustal origin could contribute to the OP activity. The source apportionment, done with the Environmental Protection Agency (EPA)—Positive Matrix Factorization (PMF5.0) model, identified six sources: secondary sulphate; biomass burning; industrial emissions; crustal; vehicle traffic and secondary nitrate; and sea spray. A MLR analysis between the source’s daily contributions and the daily DTTV values showed a reasonable agreement of the two approaches (PMF and MLR), identifying the biomass burning and the vehicle traffic and secondary nitrate as the main sources contributing to DTTV activity.

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Acidity profoundly affects almost every aspect that shapes the composition of ambient particles and their environmental impact. Thermodynamic analysis of gas-particle composition datasets offers robust estimates of acidity, but they are not available for long periods of time. Fog composition datasets, however, are available for many decades; we develop a thermodynamic analysis to estimate the ammonia in equilibrium with fog water and to infer the pre-fog aerosol pH starting from fog chemical composition and pH. The acidity values from the new method agree with the results of thermodynamic analysis of the available gasparticle composition data. Applying the new method to historical (25 years) fog water composition at the rural station of San Pietro Capofiume (SPC) in the Po Valley (Italy) suggests that the aerosol has been mildly acidic, with its pH decreasing by 0.5−1.5 pH units over the last decades. The observed pH of the fog water also increased 1 unit over the same period. Analysis of the simulated aerosol pH reveals that the aerosol acidity trend is driven by a decrease in aerosol precursor concentrations, and changes in temperature and relative humidity. Currently, NO x controls would be most effective for PM 2.5 reduction in the Po valley both during summer and winter. In the future, however, seasonal transitions to the NH 3 -sensitive region may occur, meaning that the NH 3 reduction policy may become increasingly necessary.

A novel ultrasound-assisted derivatization followed by GC/MS analysis was developed for the quantification of oxygenated organic species in ambient aerosol. Derivatization parameters mostly influencing the analytical response were investigated, i.e., solvent type, reagent concentration, and reaction duration. Response surface methodology was used to design experiments and a quadratic model was utilized to predict the variables and establish the optimal conditions. The study was performed on standard solutions of 30 compounds representing the major classes of oxygenated compounds typically found in ambient aerosol, i.e., low molecular weight carboxylic acids, sugars, and phenols. In comparison with conventional methods, the optimized procedure uses mild reaction temperature (room temperature instead of 70 °C), reduces the amount of silyl reagent (24 vs. 40 μL), and shortens derivatization times (45 vs. 70 min), participating in the current trend of analytical chemistry towards clean, green methods that reduce costs and decrease pollution. Once optimized, the ultrasound procedure was validated by assessing for repeatability, linearity, detection limits, and derivative stability. For all oxygenated organic species, the proposed method showed a good reproducibility-as the relative standard deviations (RSDs%, n = 5) of intra-day analysis were ≤7% - a good linearity with the correlation coefficients of calibration curves R ≥ 99.8, and low detection limits, ranging from 0.34 to 6.50 ng μL; thus it is suitable for its applicability in air quality monitoring. Finally, this method was successfully applied to determine 30 oxygenated organic species in three ambient PM samples collected at an urban site in Northern Italy in three different seasons. Graphical abstract Ultrasound-assisted derivatization is a green alternative method for GC/MS analysis of oxygenated organic species in atmospheric aerosol towards reduction of energy and reactive consumption.