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.

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.

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.