Source apportionment of particulate matter in a large city of southeastern Po Valley (Bologna, Italy)

Aerosol characterization and peculiarities of source apportionment in Moscow, the largest and northernmost European megacity

High population and a wide range of activities in a megacity lead to large-scale ecological consequences which require the assessment with respect to distinct characteristics of climate, location, fuel consumption, and emission sources. In-depth study of aerosol characteristics was carried out in Moscow, the largest megacity in Europe, during the cold period (autumn and winter) and in spring. PM10 chemical speciation based on carbonaceous matter, water-soluble ions, and elements was carried out to reconstruct the PM mass and evaluate the primary and secondary aerosol contribution. For the whole study period organic matter, mineral dust, and secondary inorganic/organic accounted for 34, 24, and 16 % of PM10 mass, respectively. PM10, OC, and EC approached a maximum in spring and decreased in winter. Mineral dust seasonal fraction increased from spring (17 %) to autumn (32 %), and then decreased in winter (22 %). Secondary inorganic aerosols (SIA) in opposite showed the maximum 27 % in winter. K+ marked the residential biomass burning in the region surrounding a megacity in spring and autumn, agriculture fires in spring. In winter primary aerosol contribution dropped down 56 % while secondary approached practically equal 44 %. Source factors with the relative contributions are quantified, namely city dust (26 %), traffic (23 %), industrial (20 %), biomass burning (12 %), secondary (12 %), and de-icing salt (7 %); they were significantly varying between the cold heating period and springtime. The relevance of sources to meteorological parameters and mass transportation is investigated by using both bivariate polar plots and Lagrangian integrated trajectory (HYSPLIT) model. Trajectory clustering demonstrates regional sources being crucial contributors to PM10 pollution. Aerosol speciation and source apportion factors identify the differences of the Moscow urban background among large European and Asian cities due to northern climate conditions, fast construction, long-range transport from industrial-developing area surrounding a city, regional biomass burning preferably in spring and autumn, and winter road management.

Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements

Based on the data of the State of Global Air (2020), air quality deterioration in Thailand has caused ~32,000 premature deaths, while the World Health Organization evaluated that air pollutants can decrease the life expectancy in the country by two years. PM2.5 was collected at three air quality observatory sites in Chiang-Mai, Bangkok, and Phuket, Thailand, from July 2020 to June 2021. The concentrations of 25 elements (Na, Mg, Al, Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se, Br, Sr, Ba, and Pb) were quantitatively characterised using energy-dispersive X-ray fluorescence spectrometry. Potential adverse health impacts of some element exposures from inhaling PM2.5 were estimated by employing the hazard quotient and excess lifetime cancer risk. Higher cancer risks were detected in PM2.5 samples collected at the sampling site in Bangkok, indicating that vehicle exhaust adversely impacts human health. Principal component analysis suggests that traffic emissions, crustal inputs coupled with maritime aerosols, and construction dust were the three main potential sources of PM2.5. Artificial neural networks underlined agricultural waste burning and relative humidity as two major factors controlling the air quality of Thailand.

The Impact of Russia-Ukraine geopolitical conflict on the air quality and toxicological properties of ambient PM2.5 in Milan, Italy

The geopolitical conflict between Russia and Ukraine has disrupted Europe's natural gas supplies, driving up gas prices and leading to a shift towards biomass for residential heating during colder months. This study assessed the consequent air quality and toxicological impacts in Milan, Italy, focusing on fine particulate matter (PM2.5, dp < 2.5 μm) emissions. PM2.5 samples were analyzed for their chemical composition and assessed for their oxidative potential using the dithiothreitol (DTT) assay across three periods reflecting residential heating deployment (RHD): pre-RHD, intra-RHD, and post-RHD periods. During the intra-RHD period, PM2.5 levels were significantly higher than those in other periods, with concentrations reaching 57.94 ± 7.57 μg/m3, indicating a deterioration in air quality. Moreover, levoglucosan was 9.2 times higher during the intra-RHD period compared to the pre-RHD period, correlating with elevated levels of elemental carbon (EC) and polycyclic aromatic hydrocarbons (PAHs). These findings were compared with previous local studies before the conflict, underscoring a significant rise in biomass-related emissions. DTT assay levels during the intra-RHD were 2.1 times higher than those observed during the same period in 2022, strongly correlating with biomass burning emissions. Our findings highlight the necessity for policies to mitigate the indirect health effects of increased biomass burning emissions due to the energy crisis triggered by the geopolitical conflict.

A PM10 chemically characterized nation-wide dataset for Italy. Geographical influence on urban air pollution and source apportionment

Urban textures of the Italian cities are peculiarly shaped by the local geography generating similarities among cities placed in different regions but comparable topographical districts. This suggested the following scientific question: can different topographies generate significant differences on the PM10 chemical composition at Italian urban sites that share similar geography despite being in different regions? To investigate whether such communalities can be found and are applicable at Country-scale, we propose here a novel methodological approach. A dataset comprising season-averages of PM10 mass concentration and chemical composition data was built, covering the decade 2005-2016 and referring to urban sites only (21 cities). Statistical analyses, estimation of missing data, identification of latent clusters and source apportionment modeling by Positive Matrix Factorization (PMF) were performed on this unique dataset. The first original result is the demonstration that a dataset with atypical time resolution can be successfully exploited as an input matrix for PMF obtaining Country-scale representative chemical profiles, whose physical consistency has been assessed by different tests of modeling performance. Secondly, this dataset can be considered a reference repository of season averages of chemical species over the Italian territory and the chemical profiles obtained by PMF for urban Italian agglomerations could contribute to emission repositories. These findings indicate that our approach is powerful, and it could be further employed with datasets typically available in the air pollution monitoring networks.

Experimental and in silico evaluations of the possible molecular interaction between airborne particulate matter and SARS-CoV-2

During the early stage of the COVID-19 pandemic (winter 2020), the northern part of Italy has been significantly affected by viral infection compared to the rest of the country leading the scientific community to hypothesize that airborne particulate matter (PM) could act as a carrier for the SARS-CoV-2. To address this controversial issue, we first verified and demonstrated the presence of SARS-CoV-2 RNA genome on PM2.5 samples, collected in the city of Bologna (Northern Italy) in winter 2021. Then, we employed classical molecular dynamics (MD) simulations to investigate the possible recognition mechanism(s) between a newly modelled PM2.5 fragment and the SARS-CoV-2 Spike protein. The potential molecular interaction highlighted by MD simulations suggests that the glycans covering the upper Spike protein regions would mediate the direct contact with the PM2.5 carbon core surface, while a cloud of organic and inorganic PM2.5 components surround the glycoprotein with a network of non-bonded interactions resulting in up to 4769 total contacts. Moreover, a binding free energy of -207.2 ± 3.9 kcal/mol was calculated for the PM-Spike interface through the MM/GBSA method, and structural analyses also suggested that PM attachment does not alter the protein conformational dynamics. Although the association between the PM and SARS-CoV-2 appears plausible, this simulation does not assess whether these established interactions are sufficiently stable to carry the virus in the atmosphere, or whether the virion retains its infectiousness after the transport. While these key aspects should be verified by further experimental analyses, for the first time, this pioneering study gains insights into the molecular interactions between PM and SARS-CoV-2 Spike protein and will support further research aiming at clarifying the possible relationship between PM abundance and the airborne diffusion of viruses.

Combining Satellite-Derived PM2.5 Data and a Reduced-Form Air Quality Model to Support Air Quality Analysis in US Cities

Air quality models can support pollution mitigation design by simulating policy scenarios and conducting source contribution analyses. The Intervention Model for Air Pollution (InMAP) is a powerful tool for equitable policy design as its variable resolution grid enables intra-urban analysis, the scale of which most environmental justice inquiries are levied. However, InMAP underestimates particulate sulfate and overestimates particulate ammonium formation, errors that limit the model's relevance to city-scale decision-making. To reduce InMAP's biases and increase its relevancy for urban-scale analysis, we calculate and apply scaling factors (SFs) based on observational data and advanced models. We consider both satellite-derived speciated PM2.5 from Washington University and ground-level monitor measurements from the U.S. Environmental Protection Agency, applied with different scaling methodologies. Relative to ground-monitor data, the unscaled InMAP model fails to meet a normalized mean bias performance goal of <±10% for most of the PM2.5 components it simulates (pSO4: -48%, pNO3: 8%, pNH4: 69%), but with city-specific SFs it achieves the goal benchmarks for every particulate species. Similarly, the normalized mean error performance goal of <35% is not met with the unscaled InMAP model (pSO4: 53%, pNO3: 52%, pNH4: 80%) but is met with the city-scaling approach (15%-27%). The city-specific scaling method also improves the R 2 value from 0.11 to 0.59 (ranging across particulate species) to the range of 0.36-0.76. Scaling increases the percent pollution contribution of electric generating units (EGUs) (nationwide 4%) and non-EGU point sources (nationwide 6%) and decreases the agriculture sector's contribution (nationwide -6%).

Effects of hole shape and bottom gap on the flow characteristics behind butterfly porous fence and its application in dust diffusion control in large open-air piles

In view of the possible dust pollution of atmospheric caused by large open-air piles, a scheme of using butterfly porous fences is proposed. Based on the actual cause of large open-air piles, this study makes an in-depth study on the wind shielding effect of butterfly porous fences. The effects of hole shape and bottom gap on the flow characteristics are investigated behind the butterfly porous fence with the porosity of 0.273 through the combined methods of computational fluid dynamics and validating PIV experiments. The streamlines distribution and X-velocity behind the porous fence of numerical simulation are in good agreement with the experimental results and based on the research group's previous work, the numerical model is feasible. The concept of the wind reduction ratio is proposed to quantitatively evaluate the wind shielding effect of the porous fence. The results show that the butterfly porous fence with circular holes provided the best shelter effect with the wind reduction ratio of 78.34%, and the optimal bottom gap ratio is about 0.075 with the highest wind reduction ratio of 80.1%. When a butterfly porous fence is applied on site, the diffusion range of dust in open-air piles is significantly reduced compared with that without a fence. In conclusion, the circular holes with the bottom gap ratio of 0.075 are suitable for the butterfly porous fence in practical applications and provide a solution for wind-induced control in large open-air piles.

Seasonal and Spatial Variations of the Oxidative Properties of Ambient PM2.5 in the Po Valley, Italy, before and during COVID-19 Lockdown Restrictions

This study describes the chemical and toxicological characteristics of fine particulate matter (PM_2.5) in the Po Valley, one of the largest and most polluted areas in Europe. The investigated samples were collected in the metropolitan area of Milan during the epidemic lockdown and their toxicity was evaluated by the oxidative potential (OP), measured using ascorbic acid (OP^AA) and dithiothreitol (OP^DTT) acellular assays. The study was also extended to PM_2.5 samples collected at different sites in the Po Valley in 2019, to represent the baseline conditions in the area. Univariate correlations were applied to the whole dataset to link the OP responses with the concentrations of the major chemical markers of vehicular and biomass burning emissions. Of the two assays, OP^AA was found mainly sensitive towards transition metals released from vehicular traffic, while OP^DTT towards the PM carbonaceous components. The impact of the controlling lockdown restrictions on PM_2.5 oxidative properties was estimated by comparing the OP values in corresponding time spans in 2020 and 2019. We found that during the full lockdown the OP^AA values decreased to 80-86% with respect to the OP data in other urban sites in the area, while the OP^DTT values remained nearly constant.

Apportioning PM1 in a contrasting receptor site in the Mediterranean region: Aerosol sources with an updated sulfur speciation

A multi-parametric experimental campaign was performed in Agri Valley (Basilicata, southern Italy) from July 2017 to January 2018. The investigated area, though basically rural and devoted to agricultural activities, hosts a huge on-shore oil reservoir, i.e. Centro Olio Val d'Agri (COVA), bringing substantial environmental modifications and impacts to the district landscape. Daily concentrations of PM₁ aerosol samples, Equivalent Black Carbon and number size distributions were evaluated. Chemical aerosol speciation based on elemental and ion analyses were carried out and source apportionment by Positive Matrix Factorization (PMF) was applied to reconstruct PM₁ source profile. The most significant emission sources found are torches from the oil treatment facility (37 % w/w), an unresolved factor constituted by soil resuspension, Saharan dust, and biomass burning (24 % w/w), ammonium sulphate (23 % w/w), emissions from the oil desulfurization (Claus process) (13 % w/w), and traffic + road dust (3 % w/w). SEM analysis on PM₁ single particles allowed to confirm the finding from PMF including the occurrence of elemental sulfur associated with the Claus process. The novelty of the present study consists in the identification of this latter fingerprint.

Mass concentrations and elemental analysis of PM2.5 and PM10 in a coastal Mediterranean site: A holistic approach to identify contributing sources and varying factors

PM₁₀ and PM_2.5 were measured at a suburban coastal Mediterranean site. Daily mass concentrations were generally lower than the WHO air quality limits but showed significant diurnal and seasonal variations, with intensive African dust events and residential heating emissions during wintertime causing the higher % increase of ambient concentrations (32% and 59% respectively). However, analysis of the elemental content revealed intrinsic characteristics. Statistically significant seasonal variability was found for S with higher concentrations during warm seasons directly associated with the formation of secondary sulfates. Increased S was the driving reason for the significant depletion of both Cl and Br. On the other hand, elevated K during wintertime was attributed to biomass burning. Analysis of the mineral content of airborne particles showed that typical soil-derived particles were significantly increased during dust events (Mg, Al, Si, K, Ca, Ti, Mn, Fe) although the corresponding mass concentrations preserved relative low levels (<30 μg m^-3). It was also found that dust events contributed to P, S, V, Zn, Sr and Pb with elemental ratios including Si (Si/Al, Si/Fe, Si/Ca) and Ca/Al serving as good markers for African dust. Heavy metals were found to have both direct and indirect influence on PM_2.5 and PM₁₀. PM_2.5 were primarily enriched with metals produced from motor vehicles (Cu, Zn, Pb) and ships (V, Ni), whilst, PM₁₀ enriched indirectly with Cr, Zn, Br and Pb due to road dust. At the end, source appointment has shown that the dominant contributing factor was mineral dust for both metrics (>30%) but significant contributions arose from secondary sulfates and traffic, (aged) sea salt, biomass burning (only for PM_2.5) and road dust (only for PM₁₀). Overall, this work provides a novel insight on the characteristics and chemical profile of atmospheric particles in a suburban environment largely affected by local, regional and long-range sources.

High contribution of vehicle emissions to fine particulate pollutions in Lanzhou, Northwest China based on high-resolution online data source appointment

The quantitative estimation of urban particulate matter (PM) sources is essential but limited because of various reasons. The hourly online data of PM_2.5, organic carbon (OC), elemental carbon (EC), water-soluble ions, and elements from December 2019 to November 2020 was used to conduct PM source appointment, with an emphasis on the contribution of vehicle emissions to fine PM pollution in downtown Lanzhou, Northwest China. Vehicle emissions, secondary formation, mineral dust, and coal combustion were found to be the major PM sources using the positive matrix factorization model. The seasonal mean PM_2.5 were estimated to be 72.8, 39.2, 24.3, and 43.6 μg·m^-3 and vehicle emissions accounted for 35.7%, 25.8%, 30.0%, and 56.6% in winter, spring, summer, and autumn, respectively. Vehicle emissions were the largest source of PM considering the high PM pollution in winter and its significantly large contribution in autumn. Furthermore, the contribution of vehicle emissions increased with increasing PM in winter and autumn. Vehicle emissions were also the most important source of EC, accounting for 70.3%, 91.0%, 83.5%, and 93.7% of the total EC in winter, spring, summer, and autumn, respectively. With the reduction in industrial emissions and increase in vehicle numbers in China in recent years, vehicle emissions are going to be the largest source of urban PM pollution. To sustainably improve air quality in Lanzhou and other Chinese cities, efforts should be made to control vehicle emissions such as promoting clean-energy vehicles and encouraging public transportation.

Tracing geographical origin of Lambrusco PDO wines using isotope ratios of oxygen, boron, strontium, lead and their elemental concentration

Wine identification is one of the most important aspects in the classification of wines and consumer protection. In particular, assuring wine authenticity is a crucial issue on which researchers are focusing on. This study aims to evaluate the feasibility of using chemical (B, Pb and Sr concentration) and isotopic compositions (δ¹¹B, ^20yPb/^20xPb, ⁸⁷Sr/⁸⁶Sr and δ¹⁸O) of wine samples to trace their geographic origins. Different PDO Lambrusco wines coming from a confined area of northern Italy were analyzed and all the isotopic systematics were monitored by using a multi collector inductively coupled plasma mass spectrometer (MC-ICP/MS).

The obtained results showed that boron isotope ratio measurements led to a satisfactory degree of accuracy and precision (measured value, n = 28, ¹¹B/¹⁰B of NIST SRM 951a equal to 4.04343 ± 0.00178, (u = 2s) with a certified value of 4.04362 ± 0.00136 (u = 2s). Furthermore, in the present study, it has been possible to highlight significant differences among samples by means of one-way analysis of variance (ANOVA) and post hoc Tukey-Kramer test. Finally, Principal Component Analysis (PCA) was also carried out in order to evaluate to which extent the different PDOs can be distinguished from each other, taking into account the whole set of geographical origin descriptors. Although δ¹¹B provided more sensitive information, the obtained results highlighted the important to consider the synergistic combination of all the investigated parameters to trace the different samples and the need to combine the obtained values with the same parameters evaluated in the soil, water and fertilizer as well.

•

Multi-parameter approach was used to assess wine geographical origin.

•

Validation of ¹¹B/¹⁰B measurements was accomplished by multicollector ICP/MS.

•

¹¹B/¹⁰B, ⁸⁷Sr/⁸⁶Sr, ^20yPb/^20xPb, ¹⁸O/¹⁶O, and relative elemental content, were measured in Lambrusco PDO wines.

•

Anova, Tukey-Kramer and multivariate (PCA) analysis was employed to investigate differences and similarities among samples.

•

Geographic differentiation of PDO wines resulted to be based more on B and Sr variables than Pb and O ones.

The impact of stay-home policies during Coronavirus-19 pandemic on the chemical and toxicological characteristics of ambient PM2.5 in the metropolitan area of Milan, Italy

The goal of this study was to characterize changes in components and toxicological properties of PM2.5 during the nationwide 2019-Coronavirus (COVID-19) lockdown restrictions in Milan, Italy. Time-integrated PM2.5 filters were collected at a residential site in Milan metropolitan area from April 11th to June 3rd at 2020, encompassing full-lockdown (FL), the followed partial-lockdown (PL2), and full-relaxation (FR) periods of COVID-19 restrictions. The collected filters were analyzed for elemental and organic carbon (EC/OC), water-soluble organic carbon (WSOC), individual organic species (e.g., polycyclic aromatic hydrocarbons (PAHs), and levoglucosan), and metals. According to online data, nitrogen dioxide (NO2) and benzene (C6H6) levels significantly decreased during the entire COVID-19 period compared to the same time span in 2019, mainly due to the government-backed shutdowns and curtailed road traffic. Similarly, with a few exceptions, surrogates of tailpipe emissions (e.g., traffic-associated PAHs) as well as re-suspended road dust (e.g., Fe, Mn, Cu, Cr, and Ti) were relatively lower during FL and PL2 periods in comparison with year 2019, whereas an increasing trend in mass concentration of mentioned species was observed from FL to PL2 and FR phases due to the gradual lifting of lockdown restrictions. In contrast, comparable concentrations of ambient PM2.5 and black carbon (BC) between lockdown period and the same time span in 2019 were attributed to the interplay between decreased road traffic and elevated domestic biomass burning as a result of adopted stay-home strategies. Finally, the curtailed road traffic during FL and PL2 periods led to ~25% drop in the PM2.5 oxidative potential (measured via 2',7'-dichlorodihydrofluorescein (DCFH) and dithiothreitol (DTT) assays) with respect to the FR period as well as the same time span in 2019. The results of this study provide insights into the changes in components and oxidative potential of PM2.5 in the absence of road traffic during COVID-19 restrictions.

Particulate matter emission sources and meteorological parameters combine to shape the airborne bacteria communities in the Ligurian coast, Italy

Aim of the present study is to explore how the chemical composition of particulate matter (PM) and meteorological conditions combine in shaping the air microbiome in Savona (Italy), a medium-size, heavily inhabited urban settlement, hosting a wide range of industrial activities. In particular, the air microbiome and PM₁₀ were monitored over six months in 2012. During that time, the air microbiome was highly dynamic, fluctuating between different compositional states, likely resulting from the aerosolization of different microbiomes emission sources. According to our findings, this dynamic process depends on the combination of local meteorological parameters and particle emission sources, which may affect the prevalent aerosolized microbiomes, thus representing further fundamental tools for source apportionment in a holistic approach encompassing chemical as well as microbiological pollution. In particular, we showed that, in the investigated area, industrial emissions and winds blowing from the inlands combine with an airborne microbiome which include faecal microbiomes components, suggesting multiple citizens' exposure to both chemicals and microorganisms of faecal origin, as related to landscape exploitation and population density. In conclusion, our findings support the need to include monitoring of the air microbiome compositional structure as a relevant factor for the final assessment of local air quality.

Long-term trends in the contribution of PM2.5 sources to organic carbon (OC) in the Los Angeles basin and the effect of PM emission regulations

This study aimed to investigate the long-term variations in the contributions of emission sources to ambient PM_2.5 organic carbon (OC) in central Los Angeles (CELA) and Riverside using the Chemical Speciation Network (CSN) database in the 2005-2015 period, during which several federal and state PM-based regulations were implemented to reduce tailpipe emissions in the region. The measured concentrations of OC, OC volatility fractions (i.e., OC₁, OC₂, and OC₃), elemental carbon (EC), ozone (O₃), sulfate, the ratio of potassium ion to potassium (K⁺/K), and selected metal elements were used as the input to the positive matrix factorization (PMF) model. PMF resolved tailpipe emissions, non-tailpipe emissions, secondary organic aerosols (SOA), biomass burning, and local industrial activities as the main sources contributing to ambient OC at both sampling sites. Vehicular exhaust emissions, non-tailpipe emissions, and SOA were dominant sources of OC across our sampling sites, accounting cumulatively for more than 80% of total OC mass throughout the study period. Our findings showed a significant reduction in the absolute and relative contributions of tailpipe emissions to the ambient OC levels in CELA and Riverside over the time period of 2005-2015. The contribution of exhaust emissions to total OC in CELA decreased from 3.5 µg m^-3 (49%) in 2005 to 1.5 µg m^-3 (34%) in 2015, while similar trends were observed at Riverside during this period. These reductions are mainly attributed to the implementation of several federal, state, and local air quality regulations targeting tailpipe emissions in the area. The implementation of these regulations furthermore reduced the emissions of primary organic precursors of secondary aerosols, resulting in an overall decrease (although not statistically significant, P values ranging from 0.4 to 0.6) in SOA mass concentration in both locations over the study period. In contrast to the tailpipe emissions, we observed an increasing trend (by ∼4 to 14%) in the relative contribution of non-tailpipe emissions to OC over this time period at both sites. Our results demonstrated the effectiveness of air quality regulations in reducing direct tailpipe emissions in the area, but also underpinned the need to develop equally effective mitigation policies targeting non-tailpipe PM emissions.

Deposition processes over complex topographies: Experimental data meets atmospheric modeling

The present paper describes the assessment of the atmospheric deposition processes in a basin valley through a multidisciplinary approach based on the data collected within an extensive physico-chemical characterization of the soils, combined with the local meteorology. Surface soil cores were collected on a NNW-SSE transect across the Terni basin (Central Italy), between the Monti Martani and the Monti Sabini chains (956 m a.s.l.), featuring the heavily polluted urban and industrial enclave of Terni on its bottom. Airborne radiotracers, namely ²¹⁰Pb and ¹³⁷Cs, have been used to highlight atmospheric deposition. We observed an increased deposition flux of ²¹⁰Pb and ¹³⁷Cs at sites located at the highest altitudes, and the associated concentration profiles in soil allowed to evaluate the role of atmospheric deposition. We also obtained a comprehensive dataset of stable anthropogenic pollutants of atmospheric origin that showed heterogeneity along the transect. The behavior has been explained by the local characteristic of the soil, by seeder-feeder processes promoted by the atmospheric circulation, and was reconciled with the concentration profile of radiotracers by factor analysis. Finally, the substantial impact of the local industrial activities on soil profiles and the role of the planetary boundary layer has been discussed and supported by simulations employing a Lagrangian dispersion model.

Organic molecular markers and source contributions in a polluted municipality of north-east Italy: Extended PCA-PMF statistical approach

Exceeding the maximum levels for environmental pollutants creates public and scientific interest for the environmental and human health impact it may have. In Northern Italy, the Po Valley, and in particular the Veneto region, is still a hotspot for air quality improvement. Several monitoring campaigns were carried out in this area to acquire information about sources of pollutants which are considered critical. For the first time, a deep study of the aerosol organic fraction was performed in the town Sernaglia della Battaglia, nearby Treviso. During three seasons of 2017, PM₁ and PM_2.5 samples were collected simultaneously. Organic molecular markers have been analyzed by in-situ derivatization thermal desorption gas chromatography time-of-flight mass spectrometry (IDTD-GC-TOFMS). Alkanes, polycyclic aromatic hydrocarbons, oxi-polycyclic aromatic hydrocarbons, anhydrous sugars, resins acids, triterpenoids, and acids were considered. The organic chemical composition has been analyzed based on seasonal variation and source contributions. Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) have been combined to deeply investigate the main sources of particulate organic matter. On the one hand, PCA evaluates the correlations between the organic markers and their seasonal distribution. On the other hand, the source contributions to aerosol composition are estimated by PMF. Four main emission sources were found by PMF: solid fuel combustion (coal, wood), combustion of petroleum distillates (gas and fuel oil) and exhaust gases of vehicles, industrial combustion processes, home heating, and forest fires are evaluated as the most important sources for the air quality and pollution in this municipality of Northern Italy.

How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations

Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44°30' N, 11°21' E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution.

Characterisation of atmospheric pollution near an industrial site with a biogas production and combustion plant in southern Italy

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 PM_2.5 chemical composition. High-temporal resolution measurements, supported by ancillary meteorological parameters, and source apportionment of PM_2.5 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 μm), ultrafine particles (D < 0.3 μm), accumulation (0.3 < D < 1 μm) and coarse particles (D > 1 μm). 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 PM_2.5); 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.

Hybrid multiple-site mass closure and source apportionment of PM2.5 and aerosol acidity at major cities in the Po Valley

This study investigates the major chemical components, particle-bound water content, acidity (pH), and major potential sources of PM_2.5 in major cities (Belluno, Conegliano, Vicenza, Mestre, Padua, and Rovigo) in the eastern end of the Po Valley. The measured PM_2.5 mass was reconstructed using a multiple-site hybrid chemical mass closure approach that also accounts for aerosol inorganic water content (AWC) estimated by the ISORROPIA-II model. Annually, organic matter accounted for 31-45% of the PM_2.5 at all sites, followed by nitrate (10-19%), crustal material (10-14%), sulfate (8-10%), ammonium (5-9%), elemental carbon (4-7%), other inorganic ions (3-4%), and trace elements (0.2-0.3%). Water represented 7-10% of measured PM_2.5. The ambient aerosol pH varied from 1.5 to 4.5 with lower values in summer (average in all sites 2.2 ± 0.3) and higher in winter (3.9 ± 0.3). Six major PM_2.5 sources were quantitatively identified with multiple-site positive matrix factorization: secondary sulfate (34% of PM_2.5), secondary nitrate (30%), biomass burning (17%), traffic (11%), re-suspended dust (5%), and fossil fuel combustion (3%). Biomass burning accounted for ~90% of total PAHs. Inorganic aerosol acidity was driven primarily by secondary sulfate, fossil fuel combustion (decreasing pH), secondary nitrate, and biomass burning (increasing pH). Secondary nitrate was the primary driver of the inorganic AWC variability. A concentration-weighted trajectory (multiple-site) analysis was used to identify potential source areas for the various factors and modeled aerosol acidity. Eastern and Central Europe were the main source areas of secondary species. Less acidic aerosol was associated with air masses originating from Northern Europe owing to the elevated presence of the nitrate factor. More acidic particles were observed for air masses traversing the Po Valley and the Mediterranean, possibly due to the higher contributions of fossil fuel combustion factor and the loss of nitric acid due to its interaction with coarse sea-salt particles.

Airborne particulate matter biotoxicity estimated by chemometric analysis on bacterial luminescence data

In this work, PM₁₀ samples previously subjected to thorough chemical speciation and receptor modelling, have been investigated for their bio-toxicity using an inhibition test based on bacterial luminescence modulation when in contact with airborne particulate samples. The variation of light emission intensity from a luminescent bacteria strain, the Photobacterium phosphoreum, is proposed as an efficient proxy for the quantification of bio-toxic effects induced by airborne particulate matter. PM₁₀ samples characterized by definite levels of pollutants from the pertaining air shed were found to induce a decrease in the bacterial bioluminescence intensity, expressed as percentage of Inhibition Ratio (IR%). This behaviour suggests the decay of this energy-consuming activity because of a toxic effect. Cluster analysis on chemical composition and IR% data provides evidence of a statistically significant association between the adverse effects on living cells and the range of specific chemical species in PM₁₀.

Chemical characterization of atmospheric particulate matter in Friuli Venezia Giulia (NE Italy) by exploratory data analysis with multisite and multivariate approach

The chemical composition of atmospheric particulate (PM10) in the Friuli Venezia Giulia (FVG) region (NE Italy) has been characterized for the first time with the help of exploratory data analysis (EDA) techniques (uni-, bi-, and multivariated, i.e., principal components analysis), molecular and elemental diagnostic ratios, and seasonal trends. Despite that the available analytical data was limited to the parameters routinely analyzed on PM10 by ARPA FVG (11 elements and 16 PAH congeners), the large number of samples and of measured chemical parameters, together with the applied techniques of data analysis, allowed us to extract useful latent information from the dataset, resulting in a greater knowledge of both regional and local features. Specifically, we succeeded in matching data patterns to the known pollution sources of some sampling stations, both industrial (two secondary fusion steelworks and one coke oven) and urban (traffic and domestic heating), and in defining the mainly urban or mainly industrial feature of some questionable sampling stations. This is of paramount importance to check for possible industrial inputs in urban stations, allowing policymakers to implement the most appropriate response.

Seasonal variability of PM2.5 and PM10 composition and sources in an urban background site in Southern Italy

Comparison of fine and coarse fractions in terms of sources and dynamics is scarce in southeast Mediterranean countries; differences are relevant because of the importance of natural sources like sea spray and Saharan dust advection, because most of the monitoring networks are limited to PM₁₀. In this work, the main seasonal variabilities of sources and processes involving fine and coarse PM (particulate matter) were studied at the Environmental-Climate Observatory of Lecce (Southern Italy). Simultaneous PM_2.5 and PM₁₀ samples were collected between July 2013 and July 2014 and chemically analysed to determine concentrations of several species: OC (organic carbon) and EC (elemental carbon) via thermo-optical analysis, 9 major ions via IC, and 23 metals via ICP-MS. Data was processed through mass closure analysis and Positive Matrix Factorization (PMF) receptor model characterizing seasonal variabilities of nine sources contributions. Organic and inorganic secondary aerosol accounts for 43% of PM_2.5 and 12% of PM_2.5-10 with small seasonal changes. SIA (secondary inorganic aerosol) seasonal pattern is opposite to that of SOC (secondary organic carbon). SOC is larger during the cold period, sulphate (the major contributor to SIA) is larger during summer. Two forms of nitrate were identified: NaNO₃, correlated with chloride depletion and aging of sea-spray, mainly present in PM_2.5-10; NH₄NO₃ more abundant in PM_2.5. Biomass burning is a relevant source with larger contribution during autumn and winter because of the influence of domestic heating, however, is not negligible in spring and summer, because of the contributions of fires and agricultural practices. Mass closure analysis and PMF results identify two soil sources: crustal associated to long range transport and carbonates associated to local resuspended dust. Both sources contributes to the coarse fraction and have different dynamics with crustal source contributing mainly in high winds from SE conditions and carbonates during high winds from North direction.

Tracing of aerosol sources in an urban environment using chemical, Sr isotope, and mineralogical characterization

In the framework of two national research projects (ORGANOSOL and CN-linkAIR), fine particulate matter (PM_2.5) was sampled for 17 months at an urban location in the Western European Coast. The PM_2.5 samples were analyzed for organic carbon (OC), water-soluble organic carbon (WSOC), elemental carbon (EC), major water-soluble inorganic ions, mineralogical, and for the first time in this region, strontium isotope (⁸⁷Sr/⁸⁶Sr) composition. Organic matter dominates the identifiable urban PM_2.5 mass, followed by secondary inorganic aerosols. The acquired data resulted also in a seasonal overview of the carbonaceous and inorganic aerosol composition, with an important contribution from primary biomass burning and secondary formation processes in colder and warmer periods, respectively. The fossil-related primary EC seems to be continually present throughout the sampling period. The ⁸⁷Sr/⁸⁶Sr ratios were measured on both the labile and residual PM_2.5 fractions as well as on the bulk PM_2.5 samples. Regardless of the air mass origin, the residual fractions are more radiogenic (representative of a natural crustal dust source) than the labile fractions, whose ⁸⁷Sr/⁸⁶Sr ratios are comparable to that of seawater. The ⁸⁷Sr/⁸⁶Sr ratios and the mineralogical composition data further suggest that sea salt and mineral dust are important primary natural sources of fine aerosols throughout the sampling period.

A review of AirQ Models and their applications for forecasting the air pollution health outcomes

Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects.

Source apportionment of size-fractionated particles during the 2013 Asian Youth Games and the 2014 Youth Olympic Games in Nanjing, China

In this study, samples of size-fractionated particulate matter were collected continuously using a 9-size interval cascade impactor at an urban site in Nanjing, before, during and after the Asian Youth Games (AYG), from July to September of 2013, and the Youth Olympic Games (YOG), from July to September of 2014. First, elemental concentrations, water-soluble ions including Cl^-, NO₃^-, SO₄^2-, NH₄⁺, K⁺, Na⁺ and Ca²⁺, organic carbon (OC) and elemental carbon (EC) were analysed. Then, the source apportionment of the fine and coarse particulate matter was carried out using the chemical mass balance (CMB) model. The average PM₁₀ concentrations were 90.4±20.0μg/m³ during the 2013 AYG and 70.6±25.3μg/m³ during the 2014 YOG. For PM_2.1, the average concentrations were 50.0±12.8μg/m³ in 2013 and 34.6±17.0μg/m³ in 2014. Investigations showed that the average concentrations of particles declined significantly from 2013 to 2014, and concentrations were at the lowest levels during the events. Results indicated that OC, EC, sulfate and crustal elements have significant monthly and size-based variations. The major components, including crustal elements, water-soluble ions and carbonaceous aerosol accounted for 75.3-91.9% of the total particulate mass concentrations during the sampling periods. Fugitive dust, coal combustion dust, iron dust, construction dust, soil dust, vehicle exhaust, secondary aerosols and sea salt have been classified as the main emissions in Nanjing. The source apportionment results indicate that the emissions from fugitive dust, which was the most abundance emission source during the 2013 AYG, contributed to 23.0% of the total particle mass. However, fugitive dust decreased to 6.2% of the total particle mass during the 2014 YOG. Construction dust (14.7% versus 7.8% for the AYG and the YOG, respectively) and secondary sulfate aerosol (9.3% versus 8.0% for the AYG and the YOG, respectively) showed the same trend as fugitive dust, suggesting that the mitigation measures of controlling particles from the paved roads, construction and industry worked more efficiently during the YOG.

Estimation of local and external contributions of biomass burning to PM2.5 in an industrial zone included in a large urban settlement

A total of 85 PM_2.5 samples were collected at a site located in a large industrial zone (Porto Marghera, Venice, Italy) during a 1-year-long sampling campaign. Samples were analyzed to determine water-soluble inorganic ions, elemental and organic carbon, and levoglucosan, and results were processed to investigate the seasonal patterns, the relationship between the analyzed species, and the most probable sources by using a set of tools, including (i) conditional probability function (CPF), (ii) conditional bivariate probability function (CBPF), (iii) concentration weighted trajectory (CWT), and (iv) potential source contribution function (PSCF) analyses. Furthermore, the importance of biomass combustions to PM_2.5 was also estimated. Average PM_2.5 concentrations ranged between 54 and 16 μg m^-3 in the cold and warm period, respectively. The mean value of total ions was 11 μg m^-3 (range 1-46 μg m^-3): The most abundant ion was nitrate with a share of 44 % followed by sulfate (29 %), ammonium (14 %), potassium (4 %), and chloride (4 %). Levoglucosan accounted for 1.2 % of the PM_2.5 mass, and its concentration ranged from few ng m^-3 in warm periods to 2.66 μg m^-3 during winter. Average concentrations of levoglucosan during the cold period were higher than those found in other European urban sites. This result may indicate a great influence of biomass combustions on particulate matter pollution. Elemental and organic carbon (EC, OC) showed similar behavior, with the highest contributions during cold periods and lower during summer. The ratios between biomass burning indicators (K⁺, Cl^-, NO₃^-, SO₄^2-, levoglucosan, EC, and OC) were used as proxy for the biomass burning estimation, and the contribution to the OC and PM_2.5 was also calculated by using the levoglucosan (LG)/OC and LG/PM_2.5 ratios and was estimated to be 29 and 18 %, respectively.

New Insights from Zinc and Copper Isotopic Compositions into the Sources of Atmospheric Particulate Matter from Two Major European Cities

This study reports spatial and temporal variability of Zn and Cu isotopes in atmospheric particulate matter (PM) collected in two major European cities with contrasting atmospheric pollution, Barcelona and London. We demonstrate that nontraditional stable isotopes identify source contributions of Zn and Cu and can play a major role in future air quality studies. In Barcelona, samples of fine PM were collected at street level at sites with variable traffic density. The isotopic signatures ranged between -0.13 ± 0.09 and -0.51 ± 0.05‰ for δ(66)ZnIRMM and between +0.04 ± 0.20 and +0.33 ± 0.15‰ for δ(65)CuAE633. Copper isotope signatures similar to those of Cu sulfides and Cu/Sb ratios within the range typically found in brake wear suggest that nonexhaust emissions from vehicles are dominant. Negative Zn isotopic signatures characteristic for gaseous emissions from smelting and combustion and large enrichments of Zn and Cd suggest contribution from metallurgical industries. In London, samples of coarse PM collected on the top of a building over 18 months display isotope signatures ranging between +0.03 ± 0.04 and +0.49 ± 0.02‰ for δ(66)ZnIRMM and between +0.37 ± 0.17 and +0.97 ± 0.21‰ for δ(65)CuAE633. Heavy Cu isotope signatures (up to +0.97 ± 0.21‰) and higher enrichments and Cu/Sb ratios during winter time indicate important contribution from fossil fuel combustion. The positive δ(66)ZnIRMM signatures are in good agreement with signatures characteristic for ore concentrates used for the production of tires and galvanized materials, suggesting nonexhaust emissions from vehicles as the main source of Zn pollution.

Spatial and temporal variations of trace element distribution in soils and street dust of an industrial town in NW Spain: 15years of study

Extensive spatial and temporal surveys, over 15 years, have been conducted in soil in urban parks and street dusts in one of the most polluted cities in western Europe, Avilés (NW Spain). The first survey was carried out in 1996, and since then monitoring has been undertaken every five years. Whilst the sampling site is a relatively small town, industrial activities (mainly the steel industry and Zn and Al metallurgy) and other less significant urban sources, such as traffic, strongly affect the load of heavy metals in the urban aerosol. Elemental tracers have been used to characterise the influence of these sources on the composition of soil and dust. Although PM10 has decreased over these years as a result of environmental measures undertaken in the city, some of the "industrial" elements still remain in concentrations of concern for example, up to 4.6% and 0.5% of Zn in dust and soil, respectively. Spatial trends in metals such as Zn and Cd clearly reflect sources from the processing industries. The concentrations of these elements across Europe have reduced over time, however the most recent results from Avilés revealed an upward trend in concentration for Zn, Cd, Hg and As. A risk assessment of the soil highlighted As as an element of concern since its cancer risk in adults was more than double the value above which regulatory agencies deem it to be unacceptable. If children were considered to be the receptors, then the risk nearly doubles from this element.