Understanding Airport Air Quality and Public Health Studies Related to Airports (2015)

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11 C H A P T E R 3 This chapter provides an overview of the issues and components related to understanding airport air quality contributions. 3.1 Airport Source Characteristics Airport emissions sources include those involving the combustion of fossil fuels and various fugitive sources. Emissions from mobile combustion equipment (e.g., aircraft) are generally considered the main sources at airports, but other sources also can contribute significant emissions as well. Emission characteristics depend on several factors that include, but are not limited to, the type of source (i.e., mobile, stationary, or fugitive), equipment power setting, fuel type, and pol- lution control technologies implemented. 3.1.1 Source Types and Pollutants Although other sources of emissions exist at airports, mobile sources are often the largest sources of emissions. Aircraft, as well as their auxiliary power units (APUs), ground access vehicles (GAVs), and ground support equipment (GSE) make up the bulk of emissions from mobile sources, although GSE can be both mobile and stationary. Stationary equipment sources include waste incinerators, boilers for producing heat and hot water, and power plants. When airports propose projects that require construction work (e.g., runway modifications, new terminal buildings, etc.), the emissions from construction equipment and associated activities must be accounted for as part of the project even though the emissions are temporary in nature. Like combustion-related sources (i.e., emissions from equipment exhaust), fugitive sources also must be considered. These include activities other than combustion such as maintenance activities, fuel storage operations, painting, and other activities that can result in the release of volatilized compounds. The re-entrainment of PM from the operation of mobile equipment (e.g., airport GAVs, construction equipment, etc.) and construction activities also needs to be considered. Table 3-1 provides a summary of the types of pollutants that potentially can be generated by the different sources at an airport. Although aircraft have been grouped separately, the types of pollutants emitted from combustion sources are similar even though the quantities emitted per pollutant may be different. As such, the main difference is between combustion activities and those involving fugitive emissions. Table 3-1 also provides a subset of pollutants that tend to be of primary interest with regard to health concerns. This is an indication of the pollutants that are receiving the most focus based on health concerns and continuing research. Although the criteria pollutants continue to be a concern (including the secondary formation of ozone), the current focus is largely on HAP and PM (including ultrafine) emissions. Airport Air Quality Background

12 Understanding Airport Air Quality and Public Health Studies Related to Airports 3.1.2 Equipment Power Settings Equipment power settings refer to the mode of operation of equipment such as an aircraft, GAV, or GSE. The settings are important since both the emission factors and types of pollutants emitted can vary significantly from one mode to another. For example, the following modes are typically used to describe the different power settings aircraft engines experience during normal operations at an airport: • Takeoff, • Climb out, • Approach, and • Idle/taxi. The standard power settings range from 7 percent at idle/taxi to 100 percent during takeoff. Emission factors for pollutants such as CO and hydrocarbons including HAPs tend to be higher at low power conditions while NOx emission factors tend to be higher at higher power settings (i.e., using fuel-based emission factors such as gram of pollutant per kg of fuel burned). For GSE, modes are typically not associated with the equipment. Rather, power settings in horsepower are generally used with time and power-based emission factors (e.g., gram of pollutant per horse- power per hour of equipment usage). In addition to mobile equipment, it should be noted that Table 3-1. Airport sources and associated pollutant emissions. Source Types Pollutants That Can Potentially Be Emitted Main Pollutants of Interest for Health Concerns and Research • Aircraft main engines (jet, turboprop, and piston/GA) • APU • Criteria: CO, HC/VOC, NOx, PM10, PM2.5, SOx • Criteria: Pb (only GA aircraft using AvGas) • HAPs: VOCs, aldehydes and ketones, PAHs, dioxins and furans • Ultrafine PM • Other PM species: black carbon, nitrates, sulfates • Criteria: HC/VOC, NOx, PM2.5 • Criteria: Pb (only GA aircraft using AvGas) • HAPs: VOCs, aldehydes and ketones, PAHs • Ultrafine PM • Other PM species: black carbon, nitrates, sulfates • GSE (baggage tractor, belt loader, service truck, etc.) • GAV (passenger vehicles, airport-owned vehicles, shuttle buses, etc.) • Construction—combustion (on-road and off-road equipment) • Criteria: CO, HC/VOC, NOx, PM10, PM2.5, SOx • HAPs: VOCs, aldehydes and ketones, PAHs, dioxins and furans • Ultrafine PM • Other PM species: black carbon, nitrates, sulfates • Criteria: CO, HC/VOC, NOx, PM2.5, SOx • HAPs: VOCs, aldehydes and ketones, PAHs • Stationary sources— combustion (boiler/heater, incinerator, power generator, etc.) • Training fires • Criteria: CO, HC/VOC, NOx, PM10, PM2.5, SOx • HAPs: VOCs, aldehydes and ketones, PAHs, dioxins and furans, metals, acids (metals and acids generally not associated with training fires) • Ultrafine PM • Other PM species: black carbon, nitrates, sulfates • Criteria: CO, HC/VOC, NOx, PM2.5, SOx • HAPs: VOCs, aldehydes and ketones, PAHs, dioxins and furans • Stationary sources— fugitive (maintenance, painting/coating, etc.) • Construction—fugitive (demolition, asphalt paving, wind erosion, dust re- entrainment from roadways, etc.) • Criteria: PM10, PM2.5 • HAPs: VOCs • Other PM species: black carbon, nitrates, sulfates • Criteria: PM2.5 • HAPs: VOCs

Airport Air Quality Background 13 stationary source equipment such as power plants, incinerators, etc., also have different modes of operation even though emissions from such sources are typically assessed assuming constant, average emission factors. 3.1.3 Fuel Types Several types of fuels are used at airports. Jet A is used by jet and turboprop engines while AvGas is used by piston-engine aircraft. Diesel has typically been used for GSE but electric equipment, as well as gasoline and alternative fuels, has increasingly been used for ground equipment. Jet A is denser and has a higher energy content than gasoline, but also results in greater carbon (e.g., CO2) output on a per energy basis. This does not, however, provide any implications for air pollutant emissions (especially involving CO and hydrocarbons/VOCs) as it depends on many factors including the specific combustion technologies and pollution controls used. But based on fuel content of certain chemicals such as sulfur (which is higher in Jet A as opposed to motor vehicle gasoline, for example), it can be expected that aircraft emissions may have higher SOx emissions on an energy output basis than do motor vehicles. Due to the continued use of lead in AvGas, general aviation (GA) airports have come under scrutiny for their lead contributions to local air quality. Historically, human exposures to lead have occurred through the use of lead in paints and automobile fuels (i.e., the use of tetraethyl lead in fuels to reduce engine “knocking”). Although these uses have largely been phased out, lead continues to be actively used in aviation gasoline (AvGas or 100LL). Most GA aircraft with piston engines use AvGas. Diesel fuel is typically used to power many GSE types while unleaded gasoline has generally been used for GAVs (although some GSE can use gasoline and GAVs can use diesel as well). These fuels have different characteristics that contribute to different pollutant emissions. For example, diesel has been associated with increased PM emissions. Some airports have installed charging stations that support using electric GSE. Airport buses and shuttles as well as GSE and GAVs also may use alternative fuels such as compressed natural gas (CNG). 3.1.4 Pollution Control Technologies Pollution control technologies (or pollution controls, for short) typically refer to some device or equipment that helps to reduce pollutant emissions. Aircraft engines do not have a sepa- rate piece of equipment used to control emissions. Emissions reductions are generally achieved through new combustor designs. In contrast, ground mobile equipment such as GSE and GAVs typically use catalytic material (i.e., as part of a catalytic converter) located in the exhaust system to convert pollutants such as CO and unburned hydrocarbons (including HAPs) to CO2 and water. Stationary sources (e.g., incinerators, power plants, etc.) also may use catalysts but they typically employ controls such as scrubbers and baghouses to convert or filter out pollutants depending on the size and design of the equipment/systems. 3.2 Source Emissions Contributions With all of the differences among airports, the mix of emissions contributions from sources at each airport may be different as well. There may be differences in source activities, geography, and infrastructure (e.g., airports with excellent transport infrastructure and/or a large propor- tion of freight operations may be expected to have a reduced contribution from the landside road network). Nevertheless, it is generally accepted that emissions source contributions may

14 Understanding Airport Air Quality and Public Health Studies Related to Airports be described through the following approximate rank where the first source—aircraft—are generally the highest emitters: • Aircraft in the landing and take-off (LTO) phase; • Road vehicles on airport landside roads and on the road network around the airport; • Ground support equipment (GSE); • Airport ground access vehicles (GAVs); • Aircraft auxiliary power units (APUs); • Airport heating and boiler plants; • Evaporative losses (e.g., fuel storage, maintenance, etc.); and • Airport fire training exercises. It should be noted that this is a general rank and that it is dependent on pollutant type as well and will vary by airport. For example, depending on how much of the roadways may be included in an airport air quality study, road vehicle emissions could be significantly greater than emis- sion levels from aircraft. The variation in these source contributions may be illustrated by considering the emissions generated by Airport XYZ (a fictitious airport) presented in Table 3-2. In this example, it is clear that there are many different sources that may contribute to local air quality, and that the relative magnitude of these contributions is dependent upon the pollutant of interest. This example illustrates how aircraft are generally the most significant source of emissions, but they can produce fewer emissions than GSE (e.g., CO emissions) and roadway vehicles. In fact, the off-airport roadway emissions can be significantly higher than aircraft emissions depending on roadway coverage. Depending on the layout, equipment types, and operations at each airport, the emissions inventories can be very different than this example inventory. However, in general, aircraft, GSE, and roadway vehicles tend to be the largest sources of emissions at an airport. 3.3 Airport Operations Airport operations essentially mean the activities (e.g., usage) of a source such as aircraft, GSE, boiler, etc., such that the greater the usage, the greater the magnitude of emissions. But more than that, airport operations refer to the complexities associated with analyzing source operations and the temporal impacts of the associated emissions on air quality. For example, the distribution and transport of pollutants at an airport are determined by the airport layout and the operations schedule. Airports usually have a schedule that reflects a “peak day” and “peak hour” Source Group CO VOC NOx SOx PM10 PM2.5 Aircraft 446 188 837 76 16 13 GSE 551 21 322 10 8 5 APU 37 2 32 5 - - Parking facilities 31 5 5 0.01 0.2 0.2 On-airport roadways 141 12 58 0.4 5 4 Off-airport roadways 3542 374 590 6 171 33 On-airport, airport-owned stationary sources 9 0.3 31 0.3 1.4 1.1 On-airport, not airport-owned stationary sources 15 5 7 0.3 5 4 Off-airport stationary sources 230 155 69 6 22 21 Off-road sources 932 122 341 6 21 18 Total 5934 884 2292 110 250 99 Table 3-2. On- and off-airport inventory of emissions at Airport XYZ (unit-less example values).

Airport Air Quality Background 15 of operations (e.g., Thursdays between 5:00 p.m. and 6:00 p.m.). Even the choice of runway will influence pollutant transport, as runway use is determined by prevailing winds. Emissions from other mobile sources and GSE also would likely peak (i.e., maximized usage occurs) around the same time. Airport emission trends follow a familiar pattern with decreased emissions from the indi- vidual sources due to improved design and/or efficiency, and increased emissions within source categories due to airport growth. This is the challenge for airport operators (and more broadly the aviation industry): that the growth of the airport and overall emissions will tend to exceed any operational or technological improvements for emissions reduction. An emissions inventory, usually completed on an annual basis, is used to track the amount of emissions from each source category over time including operational improvements. In contrast, air quality assessments must be performed with more detailed information taking into account appropriate temporal conditions (e.g., time of day, concentration averaging periods, etc.) to properly determine pollutant concentrations that can be compared to health benchmarks (e.g., NAAQS). This is in addition to all of the other factors including meteorology and spatial information (i.e., source and receptor locations and geography). All of the factors must be taken into account accurately when assessing air quality trends. 3.4 Geography Physical geography can play a significant role in both airport operations and local air pollutant dispersion. Ranges of mountains not only require a specific aircraft approach procedure but can define their own weather and channel air sheds to form distinct wind patterns. The emissions from airports in valleys would not tend to disperse as rapidly in comparison to emissions at airports in open terrain that experiences no major geographical hindrance to dispersion. For example, Los Angeles and LAX sit in a bowl ringed by mountains to the north and east that trap pollutants in an urban basin such that in warm weather, a cool sea breeze is drawn onshore at ground level creating a temperature inversion that prevents pollutants from dispers- ing and can result in photochemical smog. Similarly, Mexico City’s MEX Airport is situated at over 7,000 feet above mean sea level in a basin constrained by mountains with intense solar radiation; these characteristics combine to cause air quality problems involving both primary and secondary pollutants. Even with relatively flat terrain, changes in land use (e.g., urban sprawl) also may appreciably affect the surrounding meteorology through changes in the local surface energy budget (e.g., urban heat island effect) impacting diurnal air temperatures and wind patterns, thereby affecting the dispersion of pollutants. 3.5 Meteorology Wind direction and the prevailing meteorological conditions are particularly important to the way emitted air pollutants disperse. Below the mixing height (nominally about 3,000 feet above ground level), dispersion occurs based on the turbulent strength of the atmosphere (largely defined by the diurnal heating and cooling cycle) and mean wind characteristics. Overall, the daily and seasonal meteorological components that affect local concentrations of pollutants include wind direction, wind speed, mixing depth, ambient temperature, relative humidity, and solar insolation (i.e., solar energy received on a surface). Winds are of particular significance in that they determine the direction in which airport emissions will move and the area over which they will disperse. Wind patterns often demonstrate correlations with seasonality—for example, wind may flow predominately northwest in the winter

16 Understanding Airport Air Quality and Public Health Studies Related to Airports to predominantly southwest in the summer as is the case at New York’s John F. Kennedy Inter- national Airport (JFK). Similarly, predominant wind speeds may show seasonal trends. Periods of very low or nil wind may lead to stagnation near the point of emission leading to localized pollution episodes (increased concentrations). Varying wind patterns arise on a small scale as a result of the interaction of air flows with local topography, and on a larger scale from synoptic wind patterns that may be modified by differ- ential heating effects such as the sea–land breeze cycle (which is strongest in early summer but also can occur later in the year) and complex, typically nocturnal, local drainage flows. It should be noted that sea breezes may be observed even tens of miles inland. Different wind patterns at different locations are therefore to be expected, and this is reflected in the choice of runway orientations at any given airport. 3.6 Mitigation Measures for Airport Source Emissions Typically, it is the airport operator that leads the preparation and delivery of an airport air quality management plan, comprising a measurement program, air quality assessments, and various mitigation activities. However, many emission sources at an airport, and the two most significant—aircraft and access road traffic (as well as GSE in many cases)—are not within the direct control of the airport operator. Therefore, any airport mitigation plan needs to be devel- oped in collaboration with airport tenants in order to properly account for all potential sources of emissions and reductions. A range of mitigation options is available at airports to reduce local air quality pollutants. Mitigation options are typically described against each emissions source, as is the case in this section. However, mitigation options also can be considered according to the type of measure that is being implemented (see Table 3-3). In the United States, the FAA runs the Voluntary Airport Low Emission (VALE) Program. As the program title suggests, it is voluntary, and any airport in a nonattainment area is eligible to take part in the program. It provides airport operators with a legal mechanism to raise funds through their Passenger Facility Charge (PFC), and provides funding for the financing of cer- tain air quality pollutant mitigation initiatives (Airport Improvement Program funds) such as low emission vehicles, refueling and recharging facilities, and gate electrification. The FAA also created the Zero-Emissions Airport Vehicles and Infrastructure Pilot Program in 2012, which provides funds for the purchasing of zero-emissions vehicles at airports and the supporting infrastructure. In addition to the nonattainment status of an area, airport emissions reduction programs may be triggered from findings of significant impacts of non-criteria pollutants (e.g., HAPs). Like these largely voluntary measures rooted in sustainability-type programs, airports may be incen- tivized from increasing public pressure associated with the need to better understand airport contributions to local air quality and scrutiny from the public on health concerns. 3.7 Airport Emissions and Dispersion Modeling Capabilities To assess potential health impacts from airports, pollutant loading into the local and regional atmosphere, and concentrations, need to be quantified. Since measurements can be costly and may not be representative (e.g., for certain locations or time periods), modeling is necessary— for both emissions and atmospheric dispersion. The following sections provide overviews of the current state-of-the-art capabilities in these areas, as well as their limitations.

Airport Air Quality Background 17 3.7.1 Emissions Modeling The first steps in any air quality modeling work are those related to quantifying emissions. Modeling emissions for airport sources is similar to those for other industries since many of the sources are the same (e.g., GAVs are the same sources as those found on highways and boilers/ incinerators are similar to those found in industrial applications). For modeling emissions, there are two key categories of data: • Emission factors and • Activity information. Emission factors are generally in the form of mass amount of a pollutant per some unit activity. For example, grams per mile and grams per second are common units for an emission factor. These factors are specific to each pollutant and can encompass many different characteristics of a source including but not limited to the following: • Type of equipment, • Emissions control technology, • Fuel type, and • Power setting. Although some emission factors may be static (e.g., available in a data table), others may need to be modeled based on these characteristics. Once an emission factor is available, it can be applied (e.g., multiplied) with activity data to calculate emissions. The activity data represents some measure of use or operation of the source (e.g., hours of usage). Both the emission factors Options Notes Technology Technological options can be further categorized as those relating to • Fuel efficiency, • Electric equipment, • Design of engines/combustors, and • Control devices. For aircraft, technology changes are applied to the airframe or aircraft engines. Electric GSE with charging stations have been used commonly at airports to reduce fossil fuel use. The use of ground power and preconditioned air at gates is also a common practice that helps to reduce APU usage. Emissions abatement technologies are applied to road vehicles, such as catalytic convertors and particulate traps to vehicle exhaust systems. Centralized de-icing facilities can help reduce aircraft queuing near gate areas and reduce idling emissions. Fuels Alternative fuels can offer a reduction in some pollutants. Examples of alternative fuels for GSE and GAVs include compressed natural gas (CNG) and liquefied natural gas (LNG). Airport operators can consider alternative fuels (e.g., biofuels) for their vehicles. Biofuels used in aircraft also will have implications for air quality at airports. Operational Certain operational changes can reduce emissions. These include finding alternatives to travel, minimizing route distances, avoiding or reducing delays (reducing queues), minimizing weight, and using optimal power and speed. Such measures are applicable to aircraft and road vehicles. Examples may include the implementation of single-engine taxiing, towing aircraft using alternative power, and use of high-speed taxiways. Policy Policy options can be subdivided as follows: Regulatory—includes regulations that set limits on particular sources of emissions (e.g., International Civil Aviation Organization [ICAO] aircraft certification standards, road vehicle exhaust standards) or ambient pollutant concentrations (e.g., National Ambient Air Quality Standards [NAAQS]). Economic—Utilizing economic incentives and disincentives for promoting a particular course of action that is environmentally beneficial. An example is aircraft emissions charging at some airports. Voluntary—When an airport decides to mitigate the emissions of pollutants in the absence of regulatory requirements or economic incentives to do so. Table 3-3. Categorization of air pollutant emissions mitigation measures.

18 Understanding Airport Air Quality and Public Health Studies Related to Airports and activity data can be complicated—for example, they are typically dependent on power set- tings for many equipment types. Emission factors for aircraft, GSE, and GAVs are dependent on power settings (or modes of operation). Currently, the state-of-the-art emissions modeling capability for airports is represented by the FAA’s Emissions and Dispersion Modeling System (EDMS, see http://www.faa.gov/about/ office_org/headquarters_offices/apl/research/models/edms_model/), which is to be replaced by the Aviation Environmental Design Tool (AEDT, see http://www.faa.gov/about/office_org/ headquarters_offices/apl/research/models/aedt/). FAA’s long-term goal is to have AEDT encom- pass the full capabilities of EDMS (both emissions and dispersion modeling), and therefore, AEDT can be considered as a newer version of EDMS, as well as other FAA models. In keeping with this long-term view of the models, herein they are simply referred together as “EDMS/ AEDT.” The sources modeled in EDMS/AEDT are categorized as follows: • Aircraft, • Auxiliary power units (APUs), • Ground support equipment (GSE), • Ground access vehicles (GAV), • Stationary sources, and • Training fires. The underlying datasets in EDMS/AEDT were obtained from various sources and are gener- ally considered the best publicly available emission factors and activity information on a national level (i.e., for general use at all U.S. airports). However, it is recommended that specific equip- ment and activity information be obtained for each airport whenever possible to improve the accuracy of emissions inventories. Although EDMS models emission factors for GAVs, AEDT will not do so. When using AEDT to study airports, emission factors for GAVs will need to be modeled separately using the EPA’s Motor Vehicle Emissions Simulator (MOVES). Although EDMS/AEDT is considered state of the art, there are still various areas for improve- ment, some of which are currently under research (e.g., through ACRP, FAA, etc.). Users need to be mindful that uncertainties exist with the underlying modeling data and methods. To a certain extent, these uncertainties can be decreased by collecting airport-specific activity information (e.g., aircraft operations, GSE hours of usage, etc.). With the conservative nature of the model, a common tactic has been to model worst (or near-worst) cases and compare the resulting emis- sions inventories to regulatory limits such as the General Conformity de minimis levels. As such, if the worst case produces lower results than regulatory limits, then a more accurately modeled scenario would also be below the limits. This tactic can serve as both a screening approach as well as (in some cases) a means of allaying concerns over worst-case scenarios. 3.7.2 Dispersion Modeling As the name implies, dispersion modeling refers to the process of predicting the dispersion of pollutants in the atmosphere once they have been released from a source. There are differ- ent scales of assessments—for airports, local-scale (e.g., within a local community) and larger, regional scales may apply. The larger the scale (and, generally, the more time involved for dis- persion), the greater the dispersion generally resulting in lower concentrations experienced by the public for directly released pollutants. However, in each scale, secondarily formed pollutants (e.g., through atmospheric chemistry) also can impact local populations. Ozone and PM species are examples of such secondary pollutants. Much of the local-scale modeling is conducted through the use of Gaussian models. The EPA’s AERMOD modeling system (see http://www.epa.gov/ttn/scram/dispersion_prefrec.htm) is based

Airport Air Quality Background 19 on a Gaussian methodology and is the regulatory workhorse model used for most local air qual- ity assessments. AERMOD represents the state of the art in the current scientific understanding of the dispersive nature of the atmosphere. In contrast, regional-scale modeling requires the use of grid-based models such as the EPA’s Community Multiscale Air Quality (CMAQ) modeling system. Grid models are necessary since they can appropriately model atmospheric chemistry and the influence of background concentrations, whereas Gaussian models are limited in that regard. Some chemistry such as that involving NO2 can be modeled through simplified methods in Gaussian models, but ozone and secondary particulate matter formation require grid models. Although this airport dispersion modeling capability exists, relatively little dispersion model- ing work has been conducted in comparison to emissions inventory development. Most regu- latory studies (e.g., NEPA-related studies) have only required the development of emissions inventories. However, dispersion modeling is necessary to better understand potential health impacts since emissions inventories do not provide a direct correlation with pollutant concen- trations experienced by the public. Because of the additional factors affecting dispersion, predicted concentrations can have sig- nificantly greater uncertainties than emissions inventories. Concentrations are highly dependent on meteorology and the spatial relationship between sources (e.g., aircraft) and receptors (i.e., population). Any uncertainties in these factors—as well as various others such as the surround- ing geography, seasonality, source activities, etc.—can drastically affect modeled concentrations. Also, it should be noted that dispersion modeling is only as accurate as the modeled emissions will allow. That is, any uncertainties in the emissions will carry through to the concentrations. Airport air quality studies including those demonstrated in ACRP Report 71: Guidance for Quantifying the Contribution of Airport Emissions to Local Air Quality (Kim et al. 2012) illustrate the challenges of accurately predicting pollutant concentrations arising from airport emissions. As such, model users need to understand the potential limitations and uncertainties of these dispersion modeling processes. Considering all of the potential sources of uncertainty, the EPA has indicated that air quality models with predictions within a factor of two (compared to actual values) may be considered acceptable—and that it is difficult to be more accurate. It also should be noted that although alternative models exist, AERMOD is a static model generally used to predict concentrations by hour (i.e., average concentration for each hour). So although AERMOD can provide hour-by-hour concentrations, it is considered a static model due to its Gaussian plume methodology. As the need for health impact assessments increase, finer time-varying models such as those employing Gaussian puffs rather than plumes may be necessary. Such time-varying models may allow better correlations of source activities with population exposures, although the importance of this modeling refinement would depend on pollutant and health outcomes (i.e., whether short-term or long-term exposure is under consideration). 3.8 Air Quality Measurement Capabilities From the literature review conducted for this reporting, even though dispersion modeling has been conducted less than emissions inventory development, dispersion modeling has been used more to characterize air quality contributions from airports than measurements (monitoring). This is in large part due to the costs and resources required to conduct mea- surements often resulting in limitations on the number of measurement sites and samples that can be supported. Although measurements have further drawbacks of not being source- specific (difficult to assess contributions from specific sources) and have uncertainties in the monitoring equipment/methods and influences from various other factors (e.g., meteorology)

20 Understanding Airport Air Quality and Public Health Studies Related to Airports that may cause difficulties in obtaining good samples, measurements are generally considered to provide the best information because they represent real-world values. Uncertainties in measurements can vary depending on the types of equipment employed. For example, readings from continuous gas analyzers tend to be more accurate than air samples (gaseous or particulate matter) collected and analyzed over an averaging period (e.g., 1 hour, 24 hours, etc.). Although uncertainties exist, if proper measurement protocols are followed, measured concentrations will tend to be more accurate than modeled results, which can involve greater degrees of errors. An indication of the level of errors that can be expected through disper- sion modeling can be found in 40 CFR Part 51, Appendix W, which indicates that modeling is considered “reasonably reliable” if the results are within a factor of two of actual values. Appen- dix W also states, “Measurements are particularly useful in assessing the accuracy of model esti- mates. The use of air quality measurements alone however could be preferable . . . when models are found to be unacceptable and monitoring data with sufficient spatial and temporal coverage are available.” However, as previously indicated, the costs and resource requirements associated with measurements frequently make modeling more attractive. A compromise that includes both measurements and modeling is possible. For example, limited monitoring can be used to help establish background concentrations and measured data can be used to help validate modeled values. Also, measured meteorological data could be used to support more accurate modeling. Modeling can be used to provide greater spatial coverage and cover greater time periods to establish temporal trends. Generally, methods and equipment are related either to regulatory needs or research at air- ports. In terms of regulatory needs, the criteria pollutants as defined in the NAAQS dominate at U.S. airports. The promulgation of reference and equivalent measurement methods for specific pollutants also results in the type of equipment used. Table 3-4 provides a high-level overview of the most common types of measurement equipment by pollutant. 3.9 Aircraft LTO Versus Cruise Emissions Impacts For completeness, a brief overview of cruise emissions versus LTO emissions is provided in this section. The long used ICAO LTO cycle at airports includes takeoff, climb out, approach, and idle/taxi modes. These modes are defined as occurring below 3,000 feet altitude above ground level, which is nominally considered an average mixing height where an inversion layer occurs that tends to prevent the lower air (including pollutants) from mixing into the upper layers. Therefore, only the emissions occurring below this mixing height are included in an airport air quality study. Although aircraft generally continue climbing well above 3,000 feet, their flight segments above this height are defined as part of the overall cruise mode. Cruise emissions are typically excluded in airport air quality studies because they occur above the mixing height and are considered to have negligible effects on local air quality. In addition, there is no defined, stan- dard power setting for cruise but there are power settings for the LTO modes; and there are no defined emission factors for cruise. However, cruise emissions have the potential for second- ary effects on larger scales (e.g., regional, national, and global). These effects may include acid deposition, ozone formation, secondary PM, etc., and may have detrimental effects to human populations at significant distances from the airport.

Airport Air Quality Background 21 Pollutant Sampling Description Equipment CO Continuous sampling Reference or equivalent method (i.e., non- dispersive infrared) CO Short-term or hot-spot sampling Air sampling units with the reference or equivalent method used to test captured air NOx Continuous sampling Reference or equivalent method (i.e., chemiluminescence) NOx Short-term or hot-spot sampling Air sampling units with the reference or equivalent method used to test captured air (note: reactivity of gases must be considered) SOx Continuous sampling Reference or equivalent method (i.e., spectrophotochemical); note: not generally recommended at airports O3 Continuous sampling Reference or equivalent method (i.e., ultraviolet absorption) Pb Continuous sampling Reference or equivalent method (i.e., filter in high-volume sampler) Pb Short-term or hot-spot sampling Air sampling filter units PM10 and/or PM2.5 Continuous sampling Reference or equivalent method (i.e., filter with impaction specific for PM10 and/or PM2.5) PM10 and/or PM2.5 Short-term or hot-spot sampling Air sampling filter units specific for PM10 and/or PM2.5 Ultrafine PM Continuous sampling Scanning Mobility Particle Sizer (SMPS), Aerosol Time-of-Flight Mass Spectrometer (AFOTMS), or Micro-Orifice Uniform Deposit Impactor (MOUDI) Black Carbon Continuous sampling Aethalometer Black Carbon Short-term or hot-spot sampling Air sampling filter units specific for black carbon (i.e., quartz fiber filters) with elemental carbon (EC)/organic carbon (OC) analysis PM Nitrates and Sulfates Short-term or hot-spot sampling Air sampling filter units specific for black carbon (i.e., quartz fiber filters) and ion chromatography CO2 Continuous sampling Non-dispersive infrared CO2 Short-term or hot-spot sampling Air sampling units with the reference or equivalent method used to test captured air VOCs/HAPs Continuous sampling Flame ionization detector (note: not generally recommended) VOCs/HAPs Short-term or hot-spot sampling Evacuated canisters or sample cartridges; formaldehyde may be used with proportionality factors to determine other HAP concentrations PAHs Continuous sampling Photo-electric Aerosol Sensor (PAS) for particle- bound PAHs PAHs Short-term or hot-spot sampling Air sampling filter and adsorbent unit specific for PAHs and high-speed liquid chromatography (HPLC) Meteorology Continuous sampling u,v,w sonic anemometers and aspirated thermometers at two heights with appropriate data logger system; relative humidity and barometric pressure also can be measured Meteorology Short-term or hot-spot sampling u,v,w sonic anemometers with appropriate data logger Table 3-4. Air pollutant measurement equipment by pollutant.