Cover Image

Not for Sale

View/Hide Left Panel
Click for next page ( 41

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 40
40 SECTION 7 Airport Dispersion Models and Predictions A variety of models have been used for creating emission emitted butadiene reacts to form acrolein and formaldehyde inventories and predicting pollutant concentrations at vari- within 6 km of the source. Additionally, numerous VOCs, ous locations near airports. Creation of emission inventories especially aromatic compounds such as toluene and xylene, using the FAA's preferred dispersion model EDMS has been are known to form secondary organic aerosol (particulate discussed in Section 3. Here the research team focused not on matter) following atmospheric oxidation (Ng, Kroll et al. the intricacies of particular models but rather on the efficacy 2007). The secondary aerosol formed by the oxidation of of using such models for predicting HAP concentrations. 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 7.1 Emissions and Dispersion oxidation of aircraft exhaust leads to secondary aerosol is Modeling System unknown. The FAA's EDMS is a sophisticated model that has been pe- Integration of chemistry into research-grade air quality riodically updated since its inception in the 1980s. As its inputs, models is an active field of research and is necessary for accu- EDMS creates emission factors for aircraft and relies on vari- rately predicting HAP concentrations that result due to ous EPA emission inventories for non-aircraft sources (e.g., airport emissions. Two current PARTNER projects (e.g., MOBILE for on-road sources and NONROAD for APU and PARTNER Project 16, "Investigation of the Impacts of Avia- GSE emissions). EDMS relies on operator inputs for activity tion Emissions on Air Quality Impacts and PARTNER Proj- factors (e.g., time-in-mode, miles driven, etc.). The dispersion ect 11, "High-Priority Compounds Associated with Aircraft component of EDMS can be used to predict criteria pollutant Emissions") are engaged in an ambitious effort to accomplish concentrations at multiple locations near airports. Currently, this goal. These projects are intended to provide an assess- EDMS does not incorporate chemistry in its calculations. ment of air quality impacts due to aviation emissions using a A Santa Monica Municipal Airport study eschewed EDMS state-of-the-art comprehensive one-atmosphere air quality in favor of the Industrial Source Complex Short Term modeling system--the Community Multiscale Air Quality (ISCST3) model (Piazza 1999). This study (Piazza 1999) crit- (CMAQ) model--which treats gas-phase chemistry and in- icized EDMS for various reasons, because of its "limited cludes particulate matter (PM) and hazardous air pollutants capabilities" to model the dispersion of toxic pollutants (ver- (HAPs). To represent the distribution of aviation emissions sus criteria pollutants). Since 2000 EDMS has incorporated accurately in air quality modeling, they are modifying the some limited lifetime modeling abilities similar to ISCST3, Sparse Matrix Operator Kernel Emissions (SMOKE) model- but it is still a minor capability and not designed for model- ing system, which prepares emission inputs to CMAQ by ing of HAP concentrations. including three-dimensional hourly direct emissions of CO, Consideration of dispersion alone ignores the potentially NOx, THC, HAPs, SOx, and PM2.5 processed by a research important transformations that can occur due to atmo- version of the FAA's EDMS. They plan to perform annual spheric chemistry. Figure 16 depicts the atmospheric trans- base and sensitivity CMAQ simulations at multigrid resolu- formation of 1,3-butadiene in the atmosphere, which results tions focused on a few U.S. airports, and to assess the contri- in the formation of acrolein and formaldehyde. The time butions from commercial aircraft emissions to ambient air scale for this reaction can be as fast as 40 min under strong quality relative to the background air. They will also perform sunlight. With a wind speed of 3 m/s, roughly one-third of exploratory research to combine CMAQ outputs with local-

OCR for page 40
41 1, 3 Butadiene CH2OH O2-addition OH-addition CH2OH CH2OH O O two channels with NO ONO2 O2-reaction O CH2OH + HCHO + HO2 NO2 + O acrolein formaldehyde & radical propagated... Figure 16. Atmospheric processing of 1,3-butadiene. scale dispersion modeling to provide fine-scale details in the Two European models commonly used are the LASPORT vicinity of the airports. The air quality outputs of this project Emission Calculation and Dispersion Model (German Air- will subsequently be used for health impacts analysis. Prelim- port Association) and ALAQS-AV (Airport Local Air Quality inary results from these projects are just becoming available. Studies). Comparisons of models are rare. One noticeable Modeling studies in the peer-reviewed literature have exception is the work of Celikel and co-workers (Celikel, focused on the criteria pollutants--O3 (Pison and Menut Duchene et al. 2005), which compares emission inventories 2004; Unal, Hu et al. 2005), particulate matter (Unal, Hu et al. for Zurich Airport using three different methodologies. Few 2005), and NOx (Moussiopoulos, Sahm et al. 1997; Suppan studies have combined modeling with concerted measure- and Graf 2000; Farias and ApSimon 2006) with scant atten- ments, which would present a much-needed validation of the tion to HAPs. model outputs.