Evaluating the Use of Spatially Precise Diurnal Population Data in Aviation Noise Studies (2020) / Chapter Skim
Currently Skimming:
Pages 34-56
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 34... ...
34 5 Creating a Spatiotemporal Aviation Noise Study with Examples 5.1 Introduction This section presents practices and guidelines we developed for airport professionals, policymakers, and aviation noise consultants regarding the use of spatiotemporal population data. The first step is to ask how spatiotemporal population data is likely to help understand and communicate the noise impact situation around the airport in question compared to traditional methods.
|
From page 35... ...
35 night. The ESRI daytime population set can be used to study daytime noise exposure only.
|
From page 36... ...
36 of DNL in California. By definition, LAeqD and LAeqN do not include any extra weightings for noise-sensitive periods.
|
From page 37... ...
37 Figure 10: Modified Operations Count in ASIF File 5.5 Model the Noise There are two main methods for using the population data: 1) compute noise directly on the population data set by importing into AEDT as a point receptor, or 2)
|
From page 38... ...
38 population set. Then transform the population set into an ASIF file.
|
From page 39... ...
39 • AAD operations representing 570 arrivals and 570 departures. • For LAS, we modeled 1,840 arrival backbones and 917 departure backbones.
|
From page 40... ...
40 Figure 13 shows the LandScan USA population data for the same region at night. The population is notably more spread out across the metro area and the number of people in the downtown areas northwest of the airport have dispersed.
|
From page 41... ...
41 Figure 15 shows noise impact for daytime operations only (7:00 am through 9:59 pm)
|
From page 42... ...
42 Figure 17 shows the baseline and alternative tracks for nighttime operations only. Since the nighttime population is less concentrated than in the daytime and is more spread out across the city, the change in configuration is less dramatic.
|
From page 43... ...
43 Table 2 compares day versus night operations on the separate daytime and nighttime operations. The LAeqN metric, by definition, does not contain any added penalty to account for the sensitivity of nighttime operations.
|
From page 44... ...
44 nighttime noise. A synthetic 24-hour average can be computed using the formula in Equation 1 below, where D is the daytime population and N is the nighttime population for each point in the population data set.
|
From page 45... ...
45 The flight tracks represent the paths taken by actual traffic; however, the noise levels shown do not represent actual noise conditions at the airport. The San Francisco study consists of about 250 arrival backbone tracks and 470 arrival Average Annual Day (AAD)
|
From page 46... ...
46 Figure 21 shows noise contours for nighttime operations only. Noise is shown in LAeqN, which is the 9-hour weighted noise for operations from 10:00 pm through 6:59 am.
|
From page 47... ...
47 The LODES workplace population set does not include all persons but is a measure of people at a workplace by Census block location. Like the LandScan USA data set, LODES shows that there tend to be a few concentrated areas of high population density around workplaces.
|
From page 48... ...
48 Similar to the LandScan USA nighttime population set, the LODES residential population shows fewer concentrations of very high population density, and the population is more spread out across the metro area. Figure 23 shows LODES residential population and LAeqN noise from nighttime operations.
|
From page 49... ...
49 The ESRI Daytime population set shows another estimate of the areas with greatest population densities during the daytime. Figure 24 shows ESRI Daytime population and modified LAeqD noise from daytime operations.
|
From page 50... ...
50 Table 4: Sample San Francisco Day Populations Modified LAeqD LandScan USA LODES Workers ESRI Daytime <40 44,598 20,911 43,580 40-45 60,889 29,438 86,644 45-50 116,887 48,556 127,362 50-55 106,980 61,054 88,471 55-60 83,047 53,957 83,119 60-65 28,196 10,673 13,603 65-70 3,272 2,355 846 70-75 976 4,857 0 >75 4 0 0 444,849 231,801 443,625 Table 5: Sample San Francisco Night Populations LAeqN LandScan USA LODES Residential Census 2018 est <40 112,473 57,016 40,567 40-45 113,337 51,376 77,946 45-50 90,874 46,235 134,203 50-55 80,674 43,253 110,519 55-60 44,495 20,431 80,508 60-65 6,869 3,579 12,181 65-70 453 297 1,082 70-75 0 10 0 >75 0 0- 0 449,175 222,197 457,006 5.7 Existing Policy and Practices Consistency In this step, we have checked for consistency between existing regulations, policies, guidelines, and practices, and the use of these new potential analytic procedures. We have also identified which regulations, policies, guidelines, and practices would be affected when using diurnal data.
|
From page 51... ...
51 o FAA Order 1050.1, Environmental Impacts: Policies and Procedures with its Desk Reference o FAA Order 5050.4, NEPA Implementing Instructions for Airport Actions with its Desk Reference o Title 14 CFR, Part 150, Airport Noise Compatibility Planning with FAA Advisory Circular 150/5020-1, Noise Control and Compatibility Planning for Airports o FAA Order JO 7400.2, Procedures for Handling Airspace Matters, Chapter 32, Environmental Matters • Additional guidance and practices documents that assist in the aviation-related environmental review process. o International Civil Aviation Organization (ICAO)
|
From page 52... ...
52 Figure 25: Relationship of Policies and Practices In examining the various policies and practices documents, we specifically were looking for references and applications related to the use of population centroid data. As stated previously, the applicability of potentially employing diurnal population data was found to be potentially beneficial in NEPA-type studies, Part 150 studies, and for research studies.
|
From page 53... ...
53 residences (basically in the evening) , the number of people affected at various locations during different times of the day could be reported.
|
From page 54... ...
54 above DNL 60 but less than DNL 65 dB, and at or above DNL 45 dB but less than DNL 60 dB. Additionally, the analysis of potential EJ and School Learning impacts may also benefit from the use of diurnal population data.
|
From page 55... ...
55 Figure 26: Representative Noise Impact Graph Depicting Significant Changes For these studies, DNL is the mandated metric, although supporting or supplemental noise analyses may be conducted using additional metrics. Additionally, if appropriate guidelines and technical procedures are developed, it is feasible that diurnal population data could be used instead of, or as a supplement to, static population data.
|
From page 56... ...
56 As with NEPA studies, this process may be able to utilize diurnal population data as a supplement or instead of static population data to better understand the impacts. However, if it is determined to be feasible for use instead of static population data, as with NEPA, policy and regulatory decisions will need to be undertaken which would also require not just research, but validation, public comment and input, and DOT and CEQ concurrence and approval.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.