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34 Figure 13. UHC (VOC) emissions during a landing/take-off cycle. The area of each block represents the total VOC emis- sions from that phase of a landing take-of cycle. VOC emis- sions are dominated by the idle phase. The error bars indi- cate the minimum uncertainty due to lack of knowledge regarding the true thrust values used and the temperature- dependence of VOC emissions. idle for most aircraft is significantly less than 7%. Additionally, 5.2 Airport Operations the emission indices of HAPs are greatly affected by ambient conditions (temperature, relative humidity) as discussed ear- 5.2.1 Auxiliary Power Units lier. The error bars indicate the minimum uncertainty associ- Auxiliary power units (APUs) are used to provide electri- ated with those parameters. cal power to an aircraft while on the ground so that the main In order to save fuel and reduce engine noise, some air- engines can be turned off, and for starting the turbine ports and airlines encourage the practice of single-engine engines. Total use of APUs is decreasing as jet bridges are taxiing, whereby one engine is shutdown while idling. commonly outfitted with 400 Hz plug-in electrical power and According to the Chicago Department of Aviation, most conditioned air. EDMS-recommended activity factors are planes at ORD engage in the practice (Johnsson and Wash- 7 min when plug-in power is available and 26 min when it is burn 2006), and American Airlines has publicized its use of not. The total emissions, even when used for 20 min, are neg- single-engine taxiing (Arpey 2007). Furthermore, Boston ligible compared to other sources. APU emissions might be Logan Airport recommended use of the practice on a volun- relevant to the exposure of passengers inside cabin air expo- tary basis, although its prevalence is unknown (Vanasse sure or of ground service employees. Hangen Brustlin 2006). Anecdotally the practice is consid- Measurements of APU emissions are available in the lit- ered to be uncommon. erature. Emission factors can be accessed through EPA's Idle times are recorded by airports. Emission inventories, NONROAD inventory (which is used for EDMS when creat- however, are based on annual averages and only express annual ing emission inventories). emissions. Such an annual average conveys little information that is relevant to acute effects, for example, the frequency of 5.2.2 Ground Support Equipment severe delays. Outside the realm of HAPs is the criteria pollutant ozone Ground support equipment (GSE) consists of numerous (O3), which is produced by photochemical reactions involv- vehicles such as belt loaders, baggage tugs, pushback vehicles, ing VOCs and NOx. The NAAQS for ozone is an 8-hr average tractors, cabin service trucks (e.g., water, lavatory, catering, of 80 ppb. Nonattainment is based on the number of days in fuel trucks), de-icing vehicles, and airfield rescue and fire which the NAAQS is exceeded. Severe delays could also im- fighting equipment (ARFF). pact O3 concentrations, yet to our knowledge there has been EPA's NONROAD inventory and CARB's OFFROAD are no investigation of the link between delays and number of the models most commonly used for creating emission in- instances when ozone NAAQS has been exceeded. ventories, similar to the case for APUs. GSE emission factors

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35 are expressed in g/BHP-hr. Total emissions are calculated by et al. 2005), and near-roadway ambient measurements the product of the time-in-mode for each type of GSE, the (Miller, Hidy et al. 2006) provide an important supplement emission factor, the horsepower, and fractional load. The to the knowledge base. These real-world measurements have extent to which such off-road inventories accurately depict focused on criteria pollutants (CO, NOx, etc.) and only few the emissions from GSE is unknown, as are the effects of fleet studies have made HAP measurements; however, their find- age and maintenance. Variation between real-world "fleet" ings are relevant to HAP emissions as well. GSE emission factors and database values, however, is likely Although few if any on-road remote sensing studies have small compared to that observed in the on-road fleet (dis- been able to measure individual HAPs, they have been in- cussed in Section 5.2.3). Whereas the fleet emissions of on- valuable for providing information on the distribution of a road vehicles are greatly influenced by vehicles with faulty fleet's emission factors. The most noticeable result revealed emission control technology devices, the absence of such by remote-sensing measurements is that for modern gasoline- emissions control technology in most off-road engines im- fueled cars, a small fraction of vehicles is responsible for plies that the variability is expected to be minor. Nevertheless, most of the total emissions (Zhang, Stedman, et al. 1995). it is unclear if the off-road inventories used are appropriate For example, in Denver (and many other locations) ap- for airport GSE fleets. proximately 5% of the cars are responsible for 50% of the There are few peer-reviewed publications in the litera- fleet CO emissions. These vehicles are known as "super- ture regarding GSE emission factors. Among them are a emitters" or "gross-emitters," and are usually the result of study of PAH emission factors from gasoline, diesel, and poor maintenance or in some cases emission-controls tam- JP-8fueled military GSE using chassis dynamometers and pering. The emission rate of CO from a super-emitter can characterization by GC-MS. Much early work on charac- be 100 times higher than that from properly functioning terization of GSE emission was done by the Air Force vehicles. Similarly skewed distributions are observed for (Wade 2002). NOx and hydrocarbon emissions. The relative importance Most airports employ a mix of gasoline and diesel-fueled of super-emitters is likely to increase in the future as vehi- GSE. The Inherently Low Emission Airport Vehicle (ILEAV) cles become cleaner due to increasingly stringent emissions Pilot Program provided funds for replacement and/or standards. upgrades of conventionally-fueled (gasoline/diesel) GSE to The accuracy of the GAV portion of EDMS-derived inven- alternatively-fueled vehicles (FAA 2006). Upgrades of GSE tories depends on how well MOBILE can describe the actual fleets are becoming increasingly common, especially among fleet of vehicles at an airport. Since MOBILE's emission fac- airports located in polluted areas in nonattainment of the tors are based on dynamometer tests, assumptions regarding EPA's air quality standards (e.g., Dallas-Ft. Worth and LAX) the frequency of super-emitters are required. The extent to (GAO 2003). Although no longer active, the ILEAV program which MOBILE accurately reflects any given airport fleet is has been succeeded by the FAA's Voluntary Airport Low unknown. A remote-sensing study at LAX from the mid- Emission (VALE) program, which has been successful in 1990s (Klein and Saraceni 1994) indicated that the fleet of encouraging the modernization of many airports' GSE fleets taxis operated by the Bell Cab Company contained a dispro- and applicable infrastructure. portionately large number of super-emitters; subsequent investigation revealed that significant emission-control device tampering had occurred. A similar study in the late 5.2.3 Ground Access Vehicles 1990s found that taxis at ATL were among the dirtiest fleets The GAV category consists of on-road vehicles driven on recorded. The researchers' permission to operate on airport airport roadways, mostly for delivering airport passengers ground was even revoked after complaints from the taxi driv- and employees to the airport terminals and buildings. It in- ers (M. Rodgers 2007, personal communication). A different cludes but is not limited to private passenger vehicles, taxis, part of the same project found that New York taxis were rel- shuttle vans (hotel, rental car, etc.), public transportation atively clean. This story highlights the challenges presented to (buses), and security vehicles. It consists of a mix of gasoline, MOBILE in accurately characterizing on-road emissions. diesel, CNG, and electric-powered vehicles. Emission factors These uncertainties are important for determining the risk of for emission inventories typically rely on EPA's MOBILE exposure groups such as airport employees that work close to database, which relies on chassis dynamometer measure- the terminal ground traffic (as opposed to the airfield), but ments. "Real-world" measurement techniques such as on- have little effect on overall airport emissions of gas-phase road remote sensing (Zhang, Stedman et al. 1995), tunnel HAPs since aircraft at idle are the dominant HAP emitters. measurements (Miguel, Kirchstetter et al. 1998), "chase" ex- Further findings regarding the accuracy of MOBILE were periments (Herndon, Shorter et al. 2004; Herndon, Shorter presented at the recent 16th Coordinating Research Council

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36 (CRC) On-Road Vehicle Emissions Workshop (Cadle, Ayala compared to total airport emissions, which are dominated by et al. 2007): aircraft emissions at idle power. 1. MOBILE6 predicts hydrocarbon and NO emissions rea- 5.2.4 Stationary Sources sonably well for new vehicles, but underestimates hydro- carbon emissions from older vehicles; Stationary sources at airports include airport power plants 2. MOBILE6 seriously underestimates hydrocarbon emis- (HVAC systems), back-up electrical generators, parked sions at low temperatures; and motor vehicles (evaporative emissions), fuel storage and han- 3. The relative importance of nontailpipe (evaporative) emis- dling, airport restaurants, training fires, painting, solvent use, sions is highly uncertain. On-road and source apportion- and engine run-up activity. ment studies suggest that EPA and CARB models greatly Although there are large variations in the size of stationary overpredict the importance of evaporative emissions. source VOC emissions in airport emission inventories, these inventories all indicate that HAP emissions are negligible and Another technique used to assess the accuracy of MOBILE would have to be several orders of magnitude higher than relies on ambient measurements near roadways. Comparison currently believed for these sources to constitute a significant of such ambient measurements with MOBILE6 has shown (>10%) source of HAPs. The speciated HAP emission inven- that there are significant flaws in the hydrocarbon speciation. tories presented in the environmental impact statements For example, the benzene/acetylene ratio of MOBILE6 is from PHL, FLL, and ORD indicate stationary sources are of likely high by a factor of three based on comparisons with minimal importance. The one exception is toluene emissions ambient measurements (Parrish 2006). at FLL, in which 12% of total toluene emissions are ascribed Further evaluations of the EPA's National Emission to painting activities, though we note that toxicity of toluene Inventory (including on-road, nonroad, and area VOC emis- is low compared to other HAPs emitted at airports. The rele- sions) have been reviewed recently (Warneke, McKeen et al. vant national emission inventories are used for creating emis- 2007). Miller et al. states that our estimated confidence levels sion inventories (e.g., EPA's TANKS for emissions from fuel in on-road mobile HAP emissions are only "medium" storage tanks). (Miller, Hidy et al. 2006). Of the potentially large VOC (but not HAP) sources, the two largest contributions are from evaporative emissions from motor vehicles and fuel handling and storage. The VOC Activity Factors speciation of evaporative emissions closely resembles the fuel The relevant activity factors for GAV depend on the composition and is much different than that from exhaust desired level of inclusivity in an emission inventory. Some in- emissions. VOC measurements at Zurich Airport (Schur- ventories such as those at IAD (DOT, FAA et al. 2005) include mann, Schafer et al. 2007) revealed that evaporative emission only on-airport complex miles traveled, whereas others such plumes contained enhanced concentrations of aromatics and as PDX and ORD (FAA 2005; S. Hartsfield, personal com- C2-C9 alkanes but no enhancement of alkenes compared to munication) include much greater lengths of roads, depend- background concentrations. Oxygenated VOCs were not ing on the purpose of the emissions inventory. MOBILE's measured, but are likely negligible as Jet A contains a very emission factors are mileage-based, expressed in grams of small oxygenated content. pollutant per mile traveled. Since mileage-based emission factors tend to decrease with vehicle speed, some emission in- 5.2.5 De-Icing Activities ventories meticulously divide the on-road sections into smaller segments and measure vehicle speed and total vehicle The use of de-icing compounds is more a concern for counts at each roadway segment (Vanasse Hangen Brustlin water contamination than it is for air contamination. One 2006). In such studies the uncertainty in the distribution of study concluded that de-icing activities had a negligible speeds is likely smaller than the uncertainty in the fraction of impact on air quality (Celikel, Fleuti et al. 2003). Most envi- super-emitters at airports. When considering only on-airport ronmental impact studies do not even address de-icing com- miles traveled, total HAP emissions from GAV are minor pounds in air quality chapters.