Reducing the impact of lead emissions at airports
Evaluation of Pb Mitigation Strategies
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- Modeled Impacts from Moving Run-up Areas
Evaluation of Pb Mitigation StrategiesThe combination of multiple types of activities occurring in a small physical space results in Pb “hotspots.” These hotspots typically exist near the combination of the ends of runways and run-up areas. Two approaches to reduce the magnitude of these hotspot concentrations were evaluated. The first was to move the run-up areas farther away from the runway ends, which serves to spread the emissions out over a greater area so that when they mix they have smaller individual contributions. The second approach was to evaluate the impact of using MOGAS in planes and engines that are certified to use it. The following sections discuss the results of the evaluation of these two approaches, as well as the combined effectiveness of implementing both approaches. Modeled Impacts from Moving Run-up AreasModeling of aircraft lead (Pb) emissions in ACRP 02-34 Quantifying Aircraft Lead Emissions at Airports showed that the highest Pb concentrations resulted where impacts from run-up areas, takeoffs, and taxiways converged. To reduce the magnitude of these Pb hotspots, the project team proposed moving run-up areas away from the ends of runways. To evaluate this proposal, a full year of Pb modeling was performed at three airports: RVS, SMO, and PAO. Emissions were estimated for the year 2013 using the emissions inventory tool developed for ACRP Report 133: Best Practices Guidebook for Preparing Lead Emission Inventories from Piston-Powered Aircraft with the Emission Inventory Analysis Tool. Total daily aircraft activity was taken from the ATADS and scaled based on the observed aircraft activity during one month of on-site data collection at both RVS and SMO and 11 days at PAO. Emissions were spatially and temporally allocated using the activity patterns observed during the on-site data collection periods. Because weekend and weekday temporal activity patterns were statistically indistinguishable at all three airports, the same hourly activity patterns were used for all days. Fuel Pb content, times-in-mode, fuel burn rate, and the spatial distribution of emissions for RVS and SMO were also taken from observations in ACRP Web-Only Document 21:Quantifying Airport Lead Emissions at Airports and are based on airport-specific aircraft activity inventories for RVS and SMO. Observations during the development of ACRP Web-Only Document 21:Quantifying Airport Lead Emissions at Airports were used to develop surface winds criteria for assigning operations to a given end of the runways. At PAO, fuel Pb content, times-in-mode, fuel burn rate, and the spatial distribution of emissions were taken from the manual observations during the data collection period and all landings and takeoffs were assigned to Runway 31. Dispersion modeling was conducted at hourly resolution for the year 2013 using EPA’s AERMOD modeling system. Figure 8 shows the three-month average modeled concentrations at RVS (panel “a”), SMO (panel “b”), and PAO (panel “c”). The three-month average concentrations are consistent with NAAQS averaging times. Since only the year 2013 was modeled, the three-month periods of November–January and December–February were calculated using January and February 2013 modeled concentrations. Concentrations are highest during the winter months at all three airports because of relatively weaker dispersion characteristics. For each airport, the period of November–January was chosen for modeling the impact of mitigation strategies because this was the period with the maximum three-month average concentration. Figure 8 Three-Month Average Modeled Concentrations at RVS, SMO, and PAO 
Note: Since only 2013 was modeled, the three-month periods of November to January and December to February were calculated using January and February 2013 modeled concentrations. Richard Lloyd Jones Jr Airport Figure 9 shows the centroid of each of the most-used run-up areas (labeled NE-, NW-, and SW-Orig) at RVS and the two alternate locations modeled for each of these areas (labeled Z1 and Z2). These new centroids are approximately 100 meters (Z1) and 200 meters (Z2) farther away from the runway ends, but remain along the current taxiways. New modeled run-up areas were kept the same size and shape as the original areas. Figure 10 shows these three-month average concentration fields for (a) the base-case scenario of using the original run-up areas; (b) Z1 run-up areas; and (c) Z2 run-up areas. The highest concentrations modeled at RVS for these scenarios are dominated by maintenance-related engine testing emissions in the southwest portion of the airport. These emissions were observed a limited number of times that coincided with run-up data collection during the on-site data collection period. They were not observed during other activity collection periods and are likely not representative over a full year. Thus, the modeling was repeated with these emissions set to zero. Download 12.21 Mb. Share with your friends:
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