Methodology choice could affect air quality interpretation? A case study for an international airport, Marco Polo, Venice.

Venice Marco Polo Airport (VCE) is one of the most important airport of Italy, but is also placed in a delicate context; due to the proximity of the airport to the Venice historical city and the fragile ecosystem of the Lagoon that surround the city. For all these reasons the priority was to assess the possible impact of Marco Polo Airport in Venice area. For this reason a collaboration between Save Spa, the company that manage Marco Polo airport, and the Department of Environmental Sciences, Informatics and Statistics, of Ca' Foscari University was stated in order to: (I) understand the impact on air quality of an airport structure in a vulnerable context (II)analyze the airport emission trend (III) analyze how the number of flights and aircraft type can influence emission. During this collaboration two methodologies for emission estimation (EMEP-CORINAIR and Emissions and Dispersion Modeling System, EDMS) were tested in order to understand what was the best tool to estimate aircraft exhausts emissions. Results, reported in this paper show a deep difference between the two methods, with a general decrease in emission estimation using EDMS model, except in a NOxand HC cases. Subsequently the difference in emission in two typical operating days of 2009 was investigated. Results show that schedule and number of flights affect deeply emission estimation.

Influence of seasonality, air mass origin and particulate matter chemical composition on airborne bacterial community structure in the Po Valley, Italy.

The integration of chemical and biological data in aerosol studies represents a new challenge in atmospheric science. In this perspective it will be possible to gain a clearer and deeper comprehension of biogeochemical cycles in the atmosphere. In this view, this study aimed to investigate the relationships occurring between bacterial populations and PM chemical composition in one of the most polluted and urbanized areas in Europe: the Po Valley (Italy). Moreover, seasonality, long- and short-range transports were also evaluated to investigate the influence on airborne bacterial communities. PM samples were collected in two cities of the Po Valley (Milan and Venice) characterized by different meteorological conditions and atmospheric pollutant sources. Samples were analysed for water-soluble inorganic ions (WSIIs) and bacterial community structure. Chemical and biological data were jointly processed by using redundancy discriminate analysis (RDA), while the influence of atmospheric circulation was evaluated by using wind ground data and back-trajectories analysis. Results showed strong seasonal shifts of bacterial community structure in both cities, while a different behaviour was observed for air mass circulation at Milan ad Venice sites: long-range transport significantly affected bacterial populations in Milan whereas local ground wind had more influence in the Venice area. Moreover, difference in taxonomic composition can be mostly addressed to the characteristics of sampling sites. This evidence could suggest that, while PM composition is influenced by long-range transport, bacterial populations are affected, besides transport, by other factors (i.e., season and sampling site location). This perspective allow to better understand and explain airborne bacterial community behaviour.

Source apportionment of PAHs and n-alkanes bound to PM1 collected near the Venice highway.

n-Alkanes and polycyclic aromatic hydrocarbons (PAHs) bound to atmospheric particulate matter (PM1) were investigated in a traffic site located in an urban area of Venice Province (Eastern Po Valley, Italy) during the cold season. Considering the critical situation affecting the Veneto Region concerning the atmospheric pollution and the general lack of information on PM1 composition and emission in this area, this experimental study aims at determining the source profile, their relative contributions and the dispersion of finer particles. Four sources were identified and quantified using the Positive Matrix Factorization receptor model: (1) mixed combustions related to the residential activities, (2) agricultural biomass burning in addition to the resuspension of anthropogenic and natural debris carried by the wind, (3) gasoline and (4) diesel traffic-related combustions. The role of local atmospheric circulation was also investigated to identify the pollutant sources.

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 PM2.5 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 PM2.5 was also estimated. Average PM2.5 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 PM2.5 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-, SO42-, levoglucosan, EC, and OC) were used as proxy for the biomass burning estimation, and the contribution to the OC and PM2.5 was also calculated by using the levoglucosan (LG)/OC and LG/PM2.5 ratios and was estimated to be 29 and 18 %, respectively.

Analysis of the effects of meteorology on aircraft exhaust dispersion and deposition using a Lagrangian particle model.

The risk of air quality degradation is of considerable concern particularly for those airports that are located near urban areas. The ability to quantitatively predict the effects of air pollutants originated by airport operations is important for assessing air quality and the related impacts on human health. Current emission regulations have focused on local air quality in the proximity of airports. However, an integrated study should consider the effects of meteorological events, at both regional and local level, that can affect the dispersion and the deposition of exhausts. Rigorous scientific studies and extensive experimental data could contribute to the analysis of the impacts of airports expansion plans. This paper is focused on the analysis of the effects of meteorology on aircraft emission for the Marco Polo Airport in Venice. This is the most important international airport in the eastern part of the Po' Valley, one of the most polluted area in Europe. Air pollution is exacerbated by meteorology that is a combination of large and local scale effects that do not allow significant dispersion. Moreover, the airport is located near Venice, a city of noteworthy cultural and architectural relevance, and nearby the lagoon that hosts several areas of outstanding ecological importance at European level (Natura 2000 sites). Dispersion and deposit of the main aircraft exhausts (NOx, HC and CO) have been evaluated by using a Lagrangian particle model. Spatial and temporal aircraft exhaust dispersion has been analyzed for LTO cycle. Aircraft taxiing resulted to be the most impacting aircraft operation especially for the airport working area and its surroundings, however occasionally peaks may be observed even at high altitudes when cruise mode starts. Mixing height can affect concentrations more significantly than the concentrations in the exhausts themselves. An increase of HC and CO concentrations (15-50%) has been observed during specific meteorological events.

The PM2.5 chemical composition in an industrial zone included in a large urban settlement: main sources and local background.

Chemical analyses, receptor modeling and meteorological data were combined to determine the composition and sources of PM2.5 sampled daily in a large area in Italy characterized by a high number of heterogeneous industrial emissions and contiguous to a major urban center. The PM2.5 local background in the area, i.e. the common basic composition and concentrations of PM2.5, was determined. Factor analysis-multiple linear regression analysis (FA-MLRA) was used to identify and quantify the main PM sources. Groups of samples with similar source contributions were then sorted using cluster analysis. The potential source location and the influence of long range transport were investigated by using the conditional probability function (CPF) and the potential source contribution function (PSCF) respectively. On an annual basis, five sources of PM were found relevant. Industrial emissions accounted for 3% of PM mass, whereas the main contribution to PM was related to a combination of ammonium nitrate, combustion (54%) and road traffic (36%), mainly related to urban emissions. The PM2.5 background was estimated to account for 20 µg m(-3). It comprises contributions of 55% ammonium nitrate and combustion, 46% road traffic, 6% fossil fuel combustion and 3% industrial emissions. Source contributions are influenced by both local atmospheric circulation and regional transport.

IBIL analysis of road dust samples from San Bernardo tunnel.

Road dust in urban or industrial sites is an important source of atmospheric particulate by re-suspension of finer particles that may contain potentially toxic pollutants. In this work Ion Beam Induced Luminescence (IBIL), Nuclear Magnetic Resonance and fluorescence spectroscopy analyses were used to characterize road dust samples with particle size lower than 250 µm collected on the walls and on the floor of the ventilation air shaft of "Traforo del San Bernardo" highway tunnel. Moreover, for comparison, IBIL analyses were performed both on some possible anthropic sources of particulate matter and on a road dust reference sample (BCR-723). IBIL spectra as a function of the fluence were analyzed with a multivariate approach in order to identify the spectral components evolving with different rate. Nuclear Magnetic Resonance and fluorescence spectroscopy analyses were performed on extracted samples of the road dust in order to study the contribution of organic compounds to the IBIL features. Results point out that IBIL, here performed for the first time for road dust analysis, can be applied for the identification of compounds by characterizing the sample origin.

Temporal variability and effect of environmental variables on airborne bacterial communities in an urban area of Northern Italy.

Despite airborne microorganisms representing a relevant fraction of atmospheric suspended particles, only a small amount of information is currently available on their abundance and diversity and very few studies have investigated the environmental factors influencing the structure of airborne bacterial communities. In this work, we used quantitative PCR and Illumina technology to provide a thorough description of airborne bacterial communities in the urban area of Milan (Italy). Forty samples were collected in 10-day sampling sessions, with one session per season. The mean bacterial abundance was about 104 ribosomal operons per m³ of air and was lower in winter than in the other seasons. Communities were dominated by Actinobacteridae, Clostridiales, Sphingobacteriales and few proteobacterial orders (Burkholderiales, Rhizobiales, Sphingomonadales and Pseudomonadales). Chloroplasts were abundant in all samples. A higher abundance of Actinobacteridae, which are typical soil-inhabiting bacteria, and a lower abundance of chloroplasts in samples collected on cold days were observed. The variation in community composition observed within seasons was comparable to that observed between seasons, thus suggesting that airborne bacterial communities show large temporal variability, even between consecutive days. The structure of airborne bacterial communities therefore suggests that soil and plants are the sources which contribute most to the airborne communities of Milan atmosphere, but the structure of the bacterial community seems to depend mainly on the source of bacteria that predominates in a given period of time.

Using a photochemical model to assess the horizontal, vertical and time distribution of PM(2.5) in a complex area: relationships between the regional and local sources and the meteorological conditions.

A photochemical transport model has been implemented to assess the PM(2.5) spatial and temporal distribution in Venice-Mestre. This is a large city of the eastern Po Valley, which is recognized having among the highest levels of many air pollutants in Europe. This study is a first attempt to evaluate PM(2.5) distribution in such a complex ecosystem strongly affected by several different environments (the adjacent Alps, the lagoon and the sea) that create a spatial discontinuity of climate. Model performance was tested with experimental results. Samples have been collected in three sites representative of different emission characteristics. A second simulation was performed with clean boundary conditions to check the influence of the background concentrations on the study domain. Local and regional contributions were found to be strongly dependent on seasonal conditions and on local meteorology. A further analysis was conducted to predict the PM(2.5) distribution with respect to air mass movements. The non-homogeneity of surfaces affects the Planetary Boundary Layer (PBL) behavior. This consequently influences the vertical distribution of PM(2.5) especially during cold seasons and on occasion of particular meteorological events.

GC-MS analyses and chemometric processing to discriminate the local and long-distance sources of PAHs associated to atmospheric PM2.5.

PURPOSE: This study presents a procedure to differentiate the local and remote sources of particulate-bound polycyclic aromatic hydrocarbons (PAHs). METHODS: Data were collected during an extended PM(2.5) sampling campaign (2009-2010) carried out for 1 year in Venice-Mestre, Italy, at three stations with different emissive scenarios: urban, industrial, and semirural background. Diagnostic ratios and factor analysis were initially applied to point out the most probable sources. In a second step, the areal distribution of the identified sources was studied by applying the discriminant analysis on factor scores. Third, samples collected in days with similar atmospheric circulation patterns were grouped using a cluster analysis on wind data. Local contributions to PM(2.5) and PAHs were then assessed by interpreting cluster results with chemical data. RESULTS: Results evidenced that significantly lower levels of PM(2.5) and PAHs were found when faster winds changed air masses, whereas in presence of scarce ventilation, locally emitted pollutants were trapped and concentrations increased. This way, an estimation of pollutant loads due to local sources can be derived from data collected in days with similar wind patterns. Long-range contributions were detected by a cluster analysis on the air mass back-trajectories. Results revealed that PM(2.5) concentrations were relatively high when air masses had passed over the Po Valley. However, external sources do not significantly contribute to the PAHs load. CONCLUSIONS: The proposed procedure can be applied to other environments with minor modifications, and the obtained information can be useful to design local and national air pollution control strategies.

Multivariate analysis of Ion Beam Induced Luminescence spectra of irradiated silver ion-exchanged silicate glasses.

A multivariate analysis is used for the identification of the spectral features in Ion Beam Induced Luminescence (IBIL) spectra of soda-lime silicate glasses doped with silver by Ag(+)-Na(+) ion exchange. Both Principal Component Analysis and multivariate analysis were used to characterize time-evolving IBIL spectra of Ag-doped glasses, by means of the identification of the number and of the wavelength positions of the main luminescent features and the study of their evolution during irradiation. This method helps to identify the spectral features of the samples spectra, even when partially overlapped or less intense. This analysis procedure does not require additional input such as the number of peaks.

Characterization of PM10 sources in a coastal area near Venice (Italy): an application of factor-cluster analysis.

In this study a factor-cluster analysis (FCA) applied to chemical composition of atmospheric particulate matter was carried out. Relating specific wind data and back-trajectories to the daily samples grouped using FCA can be useful in atmospheric pollution studies to identify polluting sources and better interpret source apportionment results. The elemental composition and water soluble inorganic ions content of PM(10) were determined in a coastal site near Venice during the sea/land breeze season. From the factor analysis four sources were identified: mineral dust, road traffic, fossil fuels and marine aerosol. From a hierarchical cluster analysis, applied on the factor scores, samples with a similar source profile were grouped. Five clusters were identified: four with samples highly characterized by one identified source, one interpreted as general background pollution. Finally, by interpreting cluster results with wind direction data and back-trajectory analysis further detailed information was obtained on potential source locations and possible links between meteorological conditions and PM(10) chemical composition variations were detected. The proposed approach can be useful for air quality assessment studies and PM(10) reduction strategies.

Characterization of a former dump site in the Lagoon of Venice contaminated by municipal solid waste incinerator bottom ash, and estimation of possible environmental risk.

Bottom ash from a municipal solid waste incinerator on a former contaminated site, the island of Sacca San Biagio (Lagoon of Venice), was examined in order to evaluate levels of pollutants and their potential mobility and availability. Heavy metal concentrations were determined and the actual contamination of the site was compared with national legislation on polluted sites. The site was mainly contaminated by zinc, copper and lead. Physico-chemical characterization of bottom ash was carried out by SEM (Scanning Electron Microscopy) with micro-analysis by EDS (Energy Dispersive X-ray Spectroscopy) and XRD (X-ray Diffractometry), for information on newly formed minerals. SEM-EDS analysis revealed the presence of particles, compounds and clusters containing heavy metals and, in particular, the presence of barium sulfate, which was assumed to be a site-specific compound. Similarities between bottom ash and atmospheric PM10 collected on the adjacent island of Sacca Fisola were studied and a risk of aerodispersion of the fine fraction of ash was assumed. Lastly, in order to evaluate the potentially available fraction of metals (non-residual fraction) and the directly exchangeable fraction, two single extraction procedures with HCl and citric acid were carried out, respectively. Results showed a relatively low concentration of readily phyto-available metals, as well as the high concentrations found for some heavy metals (Cu, Pb, Zn) in the potentially mobilizable fraction.

Geochemical characterization of PM10 emitted by glass factories in Murano, Venice (Italy).

The atmosphere in Venice, like in other European cities, is influenced by complex PM(10) multi-emission sources with a net tendency to exceed the limits fixed by the directive 99/30/EC. This study investigated the composition of an ensemble of similar industrial sources, the Murano Glassmaking Factories (MGFs), and their influence on the Venice air quality, using a modelling approach, statistical analysis and geochemical considerations. Preliminary modelling simulations were conducted to select three sampling sites along the way of preferential transport of pollutants from source between February and April 2003. Subsequently, a sampling campaign was carried out in the same period of simulations. Concentrations of PM(10), eight major elements (Al, Ti, Ca, Mg, Na, K, Fe, Mn), 20 minor and trace elements (Li, V, Cr, Co, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Ru, Rh, Cd, Sb, Ba, Ce, Pt, Pb) and four PAHs (BaA, BbF, BkF, BaP) were quantified. The analytical results were statistically processed for exploring the relationships between inorganic elements and organic compounds, and results were interpreted using geochemical considerations. Results show a MGF component of PM(10) characterised by two different fingerprints: the first linked to glass raw material composition and the second mainly related to glass additives. Particularly, Cd, Se, As and Li preserve their ratios in all study area, and are interpreted as principal components of the MGF emissions. Other fingerprints can be traced to urban sources from the Venetian mainland.

Correlations among inorganic and organic elements in particulate matter (PM10) in urban area of Venezia-Mestre.

Concentrations of inhalable particulate matter (PM10), Pb, Zn, Pt, Ce, Cd, Se and of Benzo(a)pyrene (BaP) were determined in three locations near Venice from September 2000 to September 2001. Meteorological conditions were considered during the sampling period. All components showed higher concentrations during winter, except for Cd and Se in the two sites at Mestre. Spatial and temporal variations were observed. There were correlations between Pb and Zn and PM10, Cd and Se, Pb and BaP and, in the main street sampling site, also between BaP and Pt. Their possible sources of emission are discussed on the basis of correlations among elements.

Inter-annual variability in atmospheric input and partitioning of heavy metals in the Lagoon of Venice.

Atmospheric bulk deposition of major and trace elements was measured at Venice from November 1995 to October 1997. Collection was carried out using polyethylene bulk passive samplers, samples being collected bi-weekly. In order to highlight the contribution of the atmosphere to water chemistry and particle budgets in the Lagoon of Venice, the geochemical composition (Si, Al, Ca, Mg, K, Na, Mn, Cr, Zn, Pb, Cd, Cu, As) of dissolved and insoluble bulk fractions was determined by AAS + ICP mass spectrometry. Great sample variability was found, with almost two orders of magnitude between maximum and minimum values for several metals. All fluxes in 1995/96 were 30% lower than in 1996/97, ranging from -3% (Ca) to -57% (Li), except for Zn, Cd and As. On the contrary, the solubility of all elements decreased during 1996/97. Partitioning between soluble and insoluble phases shows that Al, Cr, Fe and Si are mainly in the insoluble form, whereas for As, Ca, Cu, Mg, Na, Ni, K, Pb and Zn the dissolved fraction represents 50-90% of total input. The amount of particle load affects partitioning between dissolved and particulate, especially for Al and Pb. Seasonal variability was evident. The lowest pH values (approximately 5.2) were recorded in winter, causing an increase of solubility for all metals except for As, which showed the highest solubility in summer.