Characterization of hourly NOx atmospheric concentrations near the Venice International Airport with additive semi-parametric statistical models
Graphical abstract
Introduction
In the last decade, several studies have been focused on the impact of rapidly growing aviation activities on the environment (e.g., Herndon et al., 2004, Yu et al., 2004, Carslaw et al., 2006, Schurmann et al., 2007, Agrawal et al., 2008, Westerdahl et al., 2008, Dodson et al., 2009, Hu et al., 2009, Lee et al., 2009, Amato et al., 2010, Kurniawan and Khardi, 2011, Mazaheri et al., 2011, Zhu et al., 2011, Hsu et al., 2012, Hsu et al., 2013, Hudda et al., 2014, Masiol and Harrison, 2014, Keuken et al., 2015). During the late 1980s and early 1990s, special attention was paid to the effects of nitrogen oxide (NOx: the sum of NO2 and NO normalized to the molecular weight) emissions on the formation of tropospheric O3 (Lee et al., 2009). Today, aviation activities are included into the Community Scheme of Allowances of Greenhouse Gases by the 2008/101/CE Directive of European Parliament and the Council of December 19th, 2008, amending the 2003/87/EC Directive. Although the aviation source provides a relatively small contribution to global air quality worsening and greenhouse gas emissions compared to other sources (FAA, Aviation and Emissions — A Primer, 2005), several studies indicate that the airport activities can have a serious impact on the air quality locally through both the emissions of aircrafts and ground support vehicles (Carslaw et al., 2006, Schurmann et al., 2007, Westerdahl et al., 2008, Dodson et al., 2009, Zhu et al., 2011, Hsu et al., 2012, Hsu et al., 2013, Hudda et al., 2014, Keuken et al., 2015).
The mean composition of plume emitted by aircraft engines is 70% CO2, something less than 30% H2O and the remainder consisting of NOx, CO, SOx, unburned or partially combusted hydrocarbons, particulates and other trace components (FAA, Aviation and Emissions — A Primer, 2005, Agrawal et al., 2008, Kinsey et al., 2011, Kurniawan and Khardi, 2011, Mazaheri et al., 2013). Although at ground level the aircraft spends most of the time at low power thrust setting, both the fuel consumed/minute and the NOx emissions greatly increase during takeoff (Herndon et al., 2004, EMEP/EEA, 2013). Specifically, NO2 is a significant fraction of NOx at idle condition for the turbofan engines that are usually employed in airliners. Vice versa, when the power thrust setting increases, the respective emission index decreases and the main constituent of NOx becomes NO (ACRP, 2008, Chapters 5–6).
From the point of view of human health, NO2 is the most troubling nitrogen oxide form (World Health Organization, 2000, World Health Organization, 2006). Short-term exposure to NO2 levels well above the typical atmospheric concentration (20–90 μg m−3) may cause defective pulmonary function, while long-term exposure to lower concentrations may cause abnormal effects in blood, spleen, liver and lungs. The negative health effects comprise cell modifications at tracheobronchial and pulmonary regions, variations in metabolism and reduction of immunological defenses against bacterial and viral infections.
Usually, road traffic was identified as an important source of NOx in urban areas (Colvile et al., 2001, Mavroidis and Chaloulakou, 2011, Lawson et al., 2011) and previous studies on NOx concentration close to Los Angeles International (Yu et al., 2004) and Heathrow International (Carslaw et al., 2006) airports highlighted that the dominant effect of the road traffic makes it difficult to detect and quantify the contribution of aircrafts to the local concentrations of NOx. Moreover, such a characterization is further complicated by the effect of weather conditions that play a key role in air pollutant dispersion. Indeed, the aircraft contributions vary in magnitude when moving a few hundred meters from the airstrip (Carslaw et al., 2006).
The aim of this study is twofold. Firstly is to illustrate statistical methods that can be fruitfully employed to evaluate the impact of aircraft NOx emissions on monitored hourly NOx concentrations in proximity to airports. Secondly is to forecast the impact associated with a potential increase of the number of flights. Although direct observations about the road traffic source are not available, the statistical approach considered in this paper is helpful to understand the different factors that contribute to the NOx emissions around an airport. The methodology is illustrated through data collected at the Venice International Airport, managed by company SAVE S.p.A. The data derive from a collaborative project of Ca' Foscari University of Venice, SAVE S.p.A and Ente Zona Industriale di Porto Marghera on monitoring the main atmospheric variables and the major pollutants near the airstrips of the Venice International Airport.
The atmospheric emission inventory of the Veneto region (Italy is subdivided into twenty administrative regions further subdivided in provinces; Venice is the capital of the Veneto region) for the years 2007/8 (INEMAR, 2013a), assessed as indicated by EMEP/EEA (2009), points out that the Venice International Airport is located in the area of the Venice province characterized by the higher NOx emissions. According to the document, the contribution of the macrosector “exhaust emissions from road transport”, that includes mopeds, motorcycles, passenger cars, buses, light and heavy duty vehicles, represents about 37% of the total emissions (INEMAR, 2013b). In the same document, the air traffic activities related to LTO cycle below about 1000 m belong to the macrosector “other mobile sources and machinery” together with military, railways, inland waterways and maritime activities that play an important role in the Venice Lagoon. The overall emission due to all these sources is quantified to be about 21%. The relative contributions for the remaining macrosectors are: Combustion in energy and transformation industries 24%; combustion in the manufacturing industry 7%; production processes 6%; non-industrial combustion plants 4%; other 1%.
The road traffic is expected to have a significant impact on the air quality worsening near the Venice International Airport given the presence of a large motorway and a series of busy roads that connect the airport to the nearby towns.
Section snippets
The sampling site
The Venice International Airport is located near the Venice Lagoon, a complex and sensitive ecosystem (Ros and Nesto, 2005, Pranovi et al., 2008, Coccioni et al., 2009) in North-Eastern Italy between the Po Valley, commonly considered the most industrialized district of Italy, and the Adriatic Sea. As discussed in Valotto et al. (2014), the area is influenced by several anthropogenic emission sources, such as the urban areas of Mestre and Venice, the industrial area of Porto Marghera, private
Selection of the best model specification
AIC statistics indicate that model specifications including a measure of air traffic volume significantly improve the quality of the model fit with respect to the baseline specification. The AIC for the baseline model specification (Eq. 2) is equal to − 3393.205. Although the first three panels of Fig. 2a are very similar, the second model specification (Eq. 5) with the additional aircraft variable yields a drop in AIC to value − 3407.665. A further improvement is obtained by the third model
Conclusions
This paper illustrates statistical methodology for the characterization of NOx concentrations in the proximity of an international airport. Differently from several papers focused on the study of pollutant concentrations around airports, we chose to work with hourly data because the variations throughout the day are informative on the concomitant sources.
In order to evaluate the airport contribution, we suggested employing additive semi-parametric statistical modeling with covariates accounting
Acknowledgments
The Authors are grateful to Professor Giancarlo Rampazzo for helpful comments. The kind permission of SAVE S.p.A. and Ente Zona Industriale del Porto di Marghera to collect the data analyzed in this paper is also acknowledged.
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