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40 A variety of models have been used for creating emission inventories and predicting pollutant concentrations at vari- ous locations near airports. Creation of emission inventories using the FAAâs preferred dispersion model EDMS has been discussed in Section 3. Here the research team focused not on the intricacies of particular models but rather on the efficacy of using such models for predicting HAP concentrations. 7.1 Emissions and Dispersion Modeling System The FAAâs EDMS is a sophisticated model that has been pe- riodically updated since its inception in the 1980s. As its inputs, EDMS creates emission factors for aircraft and relies on vari- ous EPA emission inventories for non-aircraft sources (e.g., MOBILE for on-road sources and NONROAD for APU and GSE emissions). EDMS relies on operator inputs for activity factors (e.g., time-in-mode, miles driven, etc.). The dispersion component of EDMS can be used to predict criteria pollutant concentrations at multiple locations near airports. Currently, EDMS does not incorporate chemistry in its calculations. A Santa Monica Municipal Airport study eschewed EDMS in favor of the Industrial Source Complex Short Term (ISCST3) model (Piazza 1999). This study (Piazza 1999) crit- icized EDMS for various reasons, because of its âlimited capabilitiesâ to model the dispersion of toxic pollutants (ver- sus criteria pollutants). Since 2000 EDMS has incorporated some limited lifetime modeling abilities similar to ISCST3, but it is still a minor capability and not designed for model- ing of HAP concentrations. Consideration of dispersion alone ignores the potentially important transformations that can occur due to atmo- spheric chemistry. Figure 16 depicts the atmospheric trans- formation of 1,3-butadiene in the atmosphere, which results in the formation of acrolein and formaldehyde. The time scale for this reaction can be as fast as 40 min under strong sunlight. With a wind speed of 3 m/s, roughly one-third of emitted butadiene reacts to form acrolein and formaldehyde within 6 km of the source. Additionally, numerous VOCs, especially aromatic compounds such as toluene and xylene, are known to form secondary organic aerosol (particulate matter) following atmospheric oxidation (Ng, Kroll et al. 2007). The secondary aerosol formed by the oxidation of semivolatile compounds in diesel exhaust has been shown to greatly exceed that from the known aromatic precursors (Robinson, Donahue et al. 2007). The full extent to which the oxidation of aircraft exhaust leads to secondary aerosol is unknown. Integration of chemistry into research-grade air quality models is an active field of research and is necessary for accu- rately predicting HAP concentrations that result due to airport emissions. Two current PARTNER projects (e.g., PARTNER Project 16, âInvestigation of the Impacts of Avia- tion Emissions on Air Quality Impacts and PARTNER Proj- ect 11, âHigh-Priority Compounds Associated with Aircraft Emissionsâ) are engaged in an ambitious effort to accomplish this goal. These projects are intended to provide an assess- ment of air quality impacts due to aviation emissions using a state-of-the-art comprehensive one-atmosphere air quality modeling systemâthe Community Multiscale Air Quality (CMAQ) modelâwhich treats gas-phase chemistry and in- cludes particulate matter (PM) and hazardous air pollutants (HAPs). To represent the distribution of aviation emissions accurately in air quality modeling, they are modifying the Sparse Matrix Operator Kernel Emissions (SMOKE) model- ing system, which prepares emission inputs to CMAQ by including three-dimensional hourly direct emissions of CO, NOx, THC, HAPs, SOx, and PM2.5 processed by a research version of the FAAâs EDMS. They plan to perform annual base and sensitivity CMAQ simulations at multigrid resolu- tions focused on a few U.S. airports, and to assess the contri- butions from commercial aircraft emissions to ambient air quality relative to the background air. They will also perform exploratory research to combine CMAQ outputs with local- S E C T I O N 7 Airport Dispersion Models and Predictions
scale dispersion modeling to provide fine-scale details in the vicinity of the airports. The air quality outputs of this project will subsequently be used for health impacts analysis. Prelim- inary results from these projects are just becoming available. Modeling studies in the peer-reviewed literature have focused on the criteria pollutantsâO3 (Pison and Menut 2004; Unal, Hu et al. 2005), particulate matter (Unal, Hu et al. 2005), and NOx (Moussiopoulos, Sahm et al. 1997; Suppan and Graf 2000; Farias and ApSimon 2006) with scant atten- tion to HAPs. Two European models commonly used are the LASPORT Emission Calculation and Dispersion Model (German Air- port Association) and ALAQS-AV (Airport Local Air Quality Studies). Comparisons of models are rare. One noticeable exception is the work of Celikel and co-workers (Celikel, Duchene et al. 2005), which compares emission inventories for Zurich Airport using three different methodologies. Few studies have combined modeling with concerted measure- ments, which would present a much-needed validation of the model outputs. 41 acrolein formaldehyde & radical propagated... 1, 3 Butadiene two channels with NO OH-addition O2-reaction CH2OH CH2OH CH2OH CH2OH NO2 + ONO2 O Oâ â O Oâ O2-addition + HCHO + HO2 Figure 16. Atmospheric processing of 1,3-butadiene.