Environ. Sci. Technol. 2008, 42, 1871–1876
Near-Field Commercial Aircraft Contribution to Nitrogen Oxides by Engine, Aircraft Type, and Airline by Individual Plume Sampling D A V I D C . C A R S L A W , * ,† K A R L R O P K I N S , † DUNCAN LAXEN,‡ STEPHEN MOORCROFT,‡ BEN MARNER,‡ AND MARTIN L. WILLIAMS§ Institute for Transport Studies, University of Leeds, Leeds, U.K., LS2 9JT, Air Quality Consultants, 23 Coldharbour Road, Bristol, U.K., BS6 7JT, and Department for Environment, Food and Rural Affairs, London, U.K.
Received August 2, 2007. Revised manuscript received November 16, 2007. Accepted January 4, 2008.
Nitrogen oxides (NOx) concentrations were measured in individual plumes from aircraft departing on the northern runway at Heathrow Airport in west London. Over a period of four weeks 5618 individual plumes were sampled by a chemiluminescence monitor located 180 m from the runway. Results were processed and matched with detailed aircraft movement and aircraft engine data using chromatographic techniques. Peak concentrations associated with 29 commonly used engines were calculated and found to have a good relationship with NOx emissions taken from the International Civil Aviation Organization (ICAO) databank. However, it is found that engines with higher reported NOx emissions result in proportionately lower NOx concentrations than engines with lower emissions. We show that it is likely that aircraft operational factors such as takeoff weight and aircraft thrust setting have a measurable and important effect on concentrations of NOx. For example, NOx concentrations can differ by up to 41% for aircraft using the same airframe and engine type, while those due to the same engine type in different airframes can differ by 28%. These differences are as great as, if not greater than, the reported differences in NOx emissions between different engine manufacturers for engines used on the same airframe.
Introduction Aircraft emissions are of growing importance and concern worldwide. This concern is mostly related to their impacts in the stratosphere and their growing contribution to greenhouse gas emissions (1). However, increased aircraft movements are also of concern to air pollution issues close to airports (2–5). At London Heathrow Airport (LHR), there is a specific concern over the concentrations of nitrogen dioxide (NO2) and meeting international standards for ambient NO2 concentrations (6, 7). An important consideration therefore is the development of a good understanding of the sources that contribute to local concentrations of NOx. The strong influence of ground-level road sources makes * Corresponding author phone: +44 (0) 113 343 7522; e-mail:
[email protected]. † Institute for Transport Studies, University of Leeds. ‡ Air Quality Consultants. § Department for Environment, Food and Rural Affairs. 10.1021/es071926a CCC: $40.75
Published on Web 02/20/2008
2008 American Chemical Society
the detection of aircraft emissions in time series difficult (6). Furthermore, there is a considerable lack of empirical evidence that relates the effect that different aircraft engines, aircraft types, and aircraft operation have on ground-level concentrations of pollutants. Despite the growing importance of aircraft emissions, comparatively little work has been carried out that characterizes in-use emissions from commercial aircraft, and most published work only considers relatively short field campaigns (8–12). Popp et al. sampled 122 plumes from 90 different aircraft at Heathrow under different operational conditions (takeoff, taxi and idle) (13). They used a remote sensing system that has been widely applied to vehicle exhaust measurements. The Popp et al. study, while relatively limited in terms of plumes sampled, did show that International Civil Aviation Organization (ICAO) emissions databank estimates of emission indices were consistent with their experimental findings. Herndon et al. used a tunable diode laser to measure nitric oxide (NO), NO2, and CO2 from aircraft taxiing and takeoff emissions (14). They measured plumes from 30 individual aircraft and compared three aircraft/engine combinations with emissions reported in the ICAO engine emissions databank and found good agreement with the emission indices. Wayson et al. used backscatter LIDAR to determine the initial characteristics of hot jet exhausts from commercial aircraft (15). The LIDAR work showed that plume rise is likely to be important for jet exhausts and greater than previous work suggested. There are very few reported studies that consider plume measurements from a wide range of aircraft and engine types and even fewer that consider how aircraft plumes disperse in the near-field. Most commonly, aircraft emissions are expressed as an emissions index (IE), i.e., grams of pollutant per kilogram of fuel burned. Expressing emissions in this way has the advantage of being consistent with reported emission indices in the ICAO emissions databank, which records the emissions for most modern aircraft engines (16). While emission ratios are useful for comparing with reported ICAO emissions databank estimates, they do not give an indication of the absolute contribution made by different pollutants to groundlevel concentrations, which is important for local air quality concerns. Furthermore, the variability in ground-level concentrations of pollutants due to aircraft operational factors, e.g., aircraft weight and thrust setting at takeoff, are largely unknown. Although on-airport air quality is not of direct concern for meeting international air quality limits, measurements of pollutant concentrations at these locations are very useful for developing an improved understanding of airport source and dispersion characteristics. The present study has several aims in relation to these issues. First, to determine whether individual aircraft plumes can be detected and characterized close to the airport boundary. Second, whether these plumes can be matched with aircraft movement data to understand the contribution made to ground-level NOx concentrations by aircraft and engine type. Third, to determine whether there is consistency between reported ICAO emissions data and observed concentrations of NOx and finally, to source-apportion the different emission sources contributing to measured concentrations of NOx.
Experimental Section Heathrow Airport is located 25 km west of central London close to several major motorways. Heathrow Airport has two VOL. 42, NO. 6, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Approximate layout of London Heathrow Airport showing the measurement site where the fast-response NOx instrument was located and the upwind background site at Oaks Road. runways: a northern and a southern runway separated by approximately 1.4 km. LHR operates a “runway alternation” system for noise mitigation reasons. During westerly operations (taking off and landing into the prevailing westerly wind), landing aircraft use one runway from 07:00 until 15: 00 and switch to the parallel runway from 15:00 until 23:00. Runway operation also cycles on a weekly basis. Heathrow also operates a “westerly preference” where westerly operations continue when there is a light easterly following wind up to 5 knots (2.5 m s-1), if the runways are dry and any cross-wind does not exceed 12 knots. The measurement location was situated 180 m north of the northern runway and 1600 m from the southern runway, as shown in Figure 1. An upwind (background) monitoring site is located southwest of the airport. Measurements of NOx were made between October 19 and November 15, 2005 using an Environnement SA dualchamber chemiluminescent analyzer (AC31M). The instrument uses a molybdenum converter to reduce NO2 to NO. Estimates of overall uncertainty of chemiluminescent analyzers on UK networks are about (10% (95% confidence interval) (17). It is expected that the performance of the Environnement analyzer will have achieved a similar degree of overall uncertainty. The QA/QC standards were identical to those used in the UK Automated Urban and Rural Network (17). The instrument was set up to record 10-s spot values and was located in an existing monitoring cabin as shown in Figure 1. Wind speed and direction measurements were made at the same location as the NOx measurements at a height of 4 m. Over the whole period, the wind had a southerly component when the wind blew in a direction from the northern runway toward the monitor 86% of the time. Over the period where aircraft movements were matched with NOx peaks, the mean ambient temperature was 14.2 °C (range 6.7–19.1 °C) and the mean relative humidity was 78% (range 47–97%). Information on individual aircraft movements was obtained from two sources: National Air Traffic Services (NATS) and the British Airways Authority (BAA). The NATS data provided information on individual aircraft movements including the airline, the aircraft type, the runway used, whether an aircraft was arriving or departing, and a timemarker. The time-marker represented the “wheels off the ground” or “threshold” time for departing or arriving aircraft, respectively. The BAA database consisted of similar information (not airline) but additionally reported engine type used, which could be unambiguously linked to the ICAO emissions databank. Together, these two databases provided comprehensive information on individual aircraft movements and engine types used. For convenience we refer to small and 1872
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large engine types, which we define as being below and above 150 kN rated output, respectively. Data Analysis. The data analysis addresses two principal issues. First, the extraction of the peaks due to aircraft takeoffs in the NOx time series and the calculation of peak properties including peak height, width, and area. Second, matching the time series of concentration peaks with that for aircraft movements. Peaks in NOx time series were assumed to be discrete “pollution events” associated with nearby departing aircraft. The methods applied here are modifications of methods previously developed to handle chromatographic and spectral time series (18, 19), and described in more detail elsewhere (20). Candidate NOx peak features were identified on the basis of local time series gradient inversion, i.e., d[NOx]/d[time] changes from positive to negative at a peak top and negative to positive for a peak start or end. Individual peaks were then assigned logically as peak start, top, and end sequences after the exclusion of out of-sequence events (lower of two consecutive tops or higher of two consecutive starts or ends, etc.) as peak shoulders or artifacts. Atypical peaks were modified using a set of peak shape likelihood rules. For example, a peak with large width asymmetry >50% was assumed to result from miss-assignment of the far point and foreshortened, while close peak sets (tops >50 s apart) were assumed to be clustered and fitted to a common baseline. In practice this approach could not fully account for peak clustering during periods of most intensive aircraft activity, so a median cutoff was also applied to baseline estimations to exclude atypically high baseline regions. Peak areas and heights were then calculated using the isolated peak dimensions, and all peaks
