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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 gas-particle 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, NOx controls would be most effective for PM2.5 reduction in the Po valley both during summer and winter. In the future, however, seasonal transitions to the NH3-sensitive region may occur, meaning that the NH3 reduction policy may become increasingly necessary., Please provide a synopsis

pH is a fundamental aerosol property that affects ambient particle composition, concentration and toxicity, linking pH to all aerosol environmental impacts. Direct measurement of aerosol pH is highly challenging, and so indirect proxies are often used to represent particle acidity. Aerosol thermodynamic models, such as ISORROPIA-II, are able to calculate particle pH – based on concentrations of various aerosol species, temperature (T), and relative humidity (RH) – and offer a rigorous approach to obtain aerosol pH already tested in the past with ambient aerosol data. However not many long aerosol measurements datasets exist to understand the trend of particle acidity along the past decades in Europe as well as around the world. Long-term monitoring programs for cloud/fog composition and acidity are also lacking in the global scientific community, but there are a few locations around the world where such measurements have been made routinely or periodically over periods of a decade or more. One of these locations is the rural station of San Pietro Capofiume in the Po Valley (Italy), where a consistent long dataset of fog-water ionic composition exists spanning the last 25 years (1993-2018).In this study, assuming that fog acts as an efficient natural scavenger of aerosol particles, we use the inorganic composition of fog-water collected at SPC as a proxy for the chemical composition of atmospheric aerosol in pre-fog conditions. So, we apply ISORROPIA-II to calculate the pH associated with particles having the same chemical composition of fog-water. In this way we extend the analysis to the long-time record of fog-water measurements obtaining the aerosol pH trend of the last 25 years. A comparison with existing aerosol samples and parallel ammonia gas measurements allow us to validate the approach.Our thermodynamic analysis suggests a decreasing trend of aerosol pH in Po Valley. Over the twenty-five-year period the aerosol pH decreased approximately 1.1-1.6 pH units, progressing also with an increasing rate of reduction, which corresponds to 0.18 pH units between the first and the second decades (1993-2002 and 2003-2012 respectively) and 0.44 between the decade 2003-2012 and the last 6 years (2013-2018).A multiple linear regression analysis applied on the simulated aerosol pH reveals that the aerosol pH reduction trend is driven by the contemporary decrease of the main pollutants atmospheric concentration (possibly due to the European environmental policies) and by the changing meteorogical parameters (T and RH), possibly linked with climate change.Our analysis suggests for the first time the possibility of calculating pre-fog aerosol pH using fog compositional data in a thermodynamically consistent way, which can be useful to evaluate long-term trend of particles acidity also in other region of the world for which data are available (e.g., Californian Central Valley).Projecting the trend in the future it is possible to speculate a potential change in deposition of nitrate/nitric acid from aerosol-dominant (slow) to gas-dominant (fast) with very important consequences in air quality.

Although biogas production can have some benefits, there is a research gap on potential influence of biogas plant emissions on local air quality, thus an accurate and comprehensive evaluation of impacts of this technology is needed. This study deals with this issue by means of a characterisation of air pollution near an industrial area including a biogas production (from biomass) and combustion plant located in South Italy. The methodology consists in advanced statistical analysis on concentration of gaseous pollutants, particles concentration and size distribution in number and mass, and PM2.5 chemical composition. High-temporal resolution measurements, supported by ancillary meteorological parameters, and source apportionment of PM2.5 using Positive Matrix Factorization (PMF) receptor model, are performed. The integrated approach provides the emissive picture consisting in different anthropogenic sources (i.e. traffic, biomass burning, and industrial facilities) with particular focus on biogas plant emissions. Results showed that CO and nitrogen oxides were influenced by vehicular traffic and biomass combustion, however, a contribution of the plant to NO was observed. SO2 was influenced mainly by transport from the industrial zone, but a second local contribution compatible with the emissions of the biogas plant was detected. Number particle concentrations were analysed in four size ranges: nanoparticles (D < 0.05 ?m), ultrafine particles (D < 0.3 ?m), accumulation (0.3 < D < 1 ?m) and coarse particles (D > 1 ?m). Nanoparticles and ultrafine particles were mainly influenced by vehicular traffic and biomass burning, instead, a contribution of the plant was individuated in the accumulation mode. PMF5 identified the contribution of six sources: crustal (14.7% ± 2.1% of measured PM2.5); marine aerosol (aged) (12.9% ± 2.3%); biomass burning (32.8% ± 1.4%); secondary sulphate (19.7% ± 2.4%); primary industrial emissions (5.4% ± 2.3%); traffic and secondary nitrate (17.0% ± 3.9%). The plant is likely to contribute to both sources, the industrial and the traffic plus secondary nitrate. © 2020 Elsevier B.V.

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&minus, 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)&mdash, 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&rsquo, 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.

The skin is one of the main organs exposed to airborne particulate matter (PM), which may contain various pollutants linked to a wide range of adverse health endpoints. In the present work, we analyzed the proinflammatory and oxidative effects of some PM components leading to inflammatory responses, cell proliferation or cell death. We investigated four redox-active chemicals, such as Cu (II) metal and quinones generated from polycyclic aromatic hydrocarbons (PAHs), i.e., 9,10 phenanthrenequinone and isomers 1,2 and 1,4 naphthoquinone. We performed in vitro biological tests on human keratinocyte (HaCaT) cells and also acellular assays based on the oxidation of dithiothreitol and ascorbic acid, antioxidants to assess the oxidative potential (OP). We found that treated keratinocytes showed increased activation of the redox-sensitive transcription factor NFκB and increased transcript levels of the NFκB-dependent gene IL8. Moreover, the treatment with Cu(II) and quinones increased the activities and the expression of genes involved in the redox response, SOD1 and GPX, suggesting that PM components induced cellular damage due to redox imbalances. Finally, we found alteration of the mitochondrial ultrastructure and increased apoptosis after 24 h of treatment. The results presented suggest that all of the analyzed pollutant components are able to modulate similar signal transduction pathways, resulting in activation of inflammatory processes in the skin, followed by oxidative damage. Altogether these observations indicate that exposure of skin to air pollutants modifies the redox equilibrium of keratinocytes, which could explain the increased skin damage observed in populations that live in high-pollution cities.

In this study, we investigated the cell-free ascorbic acid assay (OPAA response) to quantify the oxidative potential (OP) of particle matter (PM), as a promising metric for studying the association between the chemical properties and toxicological effects of PM. With the purpose of designing an experimental set-up mostly representative of the intracellular oxidation, the assay was performed in different media, representing an artificial respiratory tract lining fluid (RTLF), i.e., simple ascorbate (Asc) or mixtures of reduced glutathione (GSH), urate (UA) and citrate (Cit). The study was performed on real PM2.5 samples collected at an urban and rural site in the Po Valley (northern Italy). For comparison, standard solutions of redox-active species were investigated, i.e., Cu2+, Fe2+, 1,2-naphthoquinone, 1,4-naphthoquinone and 9,10-phenantrenequinone, that are known to give positive response to the AA assay. The composition of the synthetic RTLF strongly effected the OPAA responses, as they decreased with increasing the mixture complexity, following the order: Asc > Asc + Cit > Asc + UA > Asc + GSH > Asc + Cit + GSH ∼ Asc + Cit + GSH + UA. Based on comparison of the dependence of OPAA on RTLF composition, we could infer that Cu2+ and quinones were the redox active species most responsible of the OPAA response of the analysed PM2.5 samples.

The chemical composition and oxidative potential (OP) of particulate matter (PM10) samples were investigated at an industrial (Ala) and a background (TN) site in northern Italy. Three emission sources of airborne metals were identified by Positive Matrix Factorization (PMF) analysis, i.e., the zinc coating facility located in the area, the traffic on the nearby motorway and the pesticides normally used in the extensive vineyard cultivation. PM10 redox activity was measured using dithiothreitol (OPDTTV) and ascorbic acid (OPAAV) cell-free assays. Similar OPDTTV responses were obtained at the two sites (0.60 ± 0.23 mmol min−1 m−3), while higher (OPAAV) values were measured at Ala (1.4 ± 1.1 nmol min−1 m−3) than at TN (0.7 ± 0.4 nmol min−1 m−3). Overall, both OPDTTV and OPAAV responses were found to be broadly correlated with several inorganic species, namely ions and soluble metals, and organic components. In particular, OPAAV responses are mainly affected by Zn directly emitted from the zinc factory and Cu used in the vineyard cultivation. Therefore, the higher OPAAV values measured at Ala can be explained by the higher concentration of these metals at the industrial site.

An extended study on the oxidative potential (OP) of PM10 particles collected from December 2014 to October 2015 at a peninsular site of the Central Mediterranean basin has been performed. PM10 particles have been selected to better account for all different aged/fresh particle types. Two acellular assays, i.e., the dithiothreitol (DTT) and ascorbic acid (AA) methods, were used to measure the OP of PM10 particles chemically speciated by more than 40 species. DTT and AA assays provide close mean values of volume normalized OPV responses, with similar variability range, i.e., mean OPDTTV = 0.24 ± 0.12 nmolDTT min−1 m−3 and mean OPAAV = 0.29 ± 0.18 nmolAA min−1 m−3. Also mass normalized OPm responses are similar for both assays, with mean value close to 0.008 nmol min−1 μg−1. The measured OPDTTV and OPAAV are correlated with several inorganic species, namely ions and metals, and with organic/elemental carbon. The discrimination of the data according seasonality, i.e., Autumn-Winter (AW, October–March) and Spring-Summer (SS, April–September) days, shows a clear seasonal trend of correlation coefficients. In AW, OPDTTV is strongly correlated with nss-K+ and nss-Ca2+, in addition to Ba, Cd, Ce, Cr, Cu, Fe, and Mn (traffic-related metals) and with EC, OC, and POC associated with the traffic exhaust source and/or with the combustion including biomass-burning source. Otherwise, OPDTTV of SS samples is correlated only with NH4+, Cu, EC, OC, and POC. The OPAAV of AW samples is well correlated with Ba, Ce, Cr, Cu, Fe, Mn, nss-K+, EC, OC, and POC, which are related with traffic and/or combustion emissions. Conversely, in SS, OPAAV is mainly correlated with NH4+, nss-K+, nss-Mg2+, nss-Ca2+, nss-SO42−, Cu, Mn, P, Pb, and oxalate, that are species related to secondary aerosols and resuspended soil from vehicular traffic and/or transported Saharan dust. These findings point the importance of both organic components and transition metals to PM oxidative properties, and also suggest that synergistic/antagonistic interactions and cross-correlations between the PM redox-active components are likely responsible for the seasonal variation of the AA and DTT assay response. The inter-correlation among all analysed species has been investigated to explain contrasting results and the negative correlations between OP values and some chemical species.

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 2 ≥ 99.8, and low detection limits, ranging from 0.34 to 6.50 ng μL-1; 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 PM2.5 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.