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From page 46... ... Appendix B Data Modeled for Noise Predictions Read the entire page →
From page 47... ... Appendix B – Data Modeled for Noise Predictions B-1 The following appendix provides a summary of input data used to produce the modeled noise metrics presented in Chapter 4. HMMH has developed a preprocessor named RealContoursTM that converts radar flight tracks to Integrated Noise Model (INM) tracks, thereby modeling each and every radar flight as an INM flight track and producing daily contours, which are then averaged to provide annual noise metrics. RealContoursTM uses individual flight tracks taken directly from radar systems rather than relying on consolidated, representative flight track data. This provides the advantage of modeling each aircraft operation on the specific runway it actually used and at the actual time of day of the arrival or departure. RealContoursTM then sets up an INM study for each day using the INM standard data. Each day is then modeled in the INM and the results for each day combined and averaged to get the annual DNL contours. The RealContoursTM approach essentially eliminates the approximation associated with the use of a limited set of prototypical modeling tracks by applying the INM's modeling capabilities on a flight‐by‐flight basis for over 138,000 tracks. This methodology, including the use of RealContoursTM, has been used for a variety of other FAA‐funded and reviewed projects including NEM projects at a number of airports. Modeled data for runway ends entered into RealContours™ are presented in Table B‐1. Table B‐1. Runway Data Runway Latitude Longitude Elevation (ft. MSL) Read the entire page →
From page 48... ... Appendix B – Data Modeled for Noise Predictions B-2 Table B‐2. Operations by Aircraft Type Aircraft Type No. Day Operations No. Night Operations Total Operations 1900D 2,363 150 2,513 717200 16,252 1,197 17,449 727D17 1 0 1 727EM1 10 5 15 727EM2 88 4 92 727Q15 5 1 6 727Q9 4 0 4 737300 15,733 2,050 17,783 7373B2 966 125 1,091 737400 2,345 300 2,645 737500 34 12 46 737700 53,865 7,641 61,506 737800 94,904 25,573 120,477 737N17 11 7 18 747200 40 178 218 74720A 26 89 115 74720B 64 210 274 747400 4,465 2,708 7,173 7478 1,553 2,032 3,585 757300 6,533 2,161 8,694 757PW 16,168 5,608 21,776 757RR 6,747 1,644 8,391 767300 12,473 5,683 18,156 767400 54 21 75 767CF6 77 487 564 767JT9 43 727 770 777200 5,829 2,206 8,035 777300 1,125 216 1,341 7773ER 18,119 7,230 25,349 7878R 7,689 1,468 9,157 A109 61 2 63 A300‐622R 544 722 1,266 A300B4‐203 36 393 429 A310‐304 14 1 15 A319‐131 28,559 6,227 34,786 A320‐211 26,547 3,958 30,505 A320‐232 15,271 5,489 20,760 A321‐232 33,830 12,052 45,882 A330‐301 4,799 1,691 6,490 A330‐343 216 0 216 A340‐211 2,550 391 2,941 A340‐642 1,237 127 1,364 A380‐841 3,620 1,747 5,367 A380‐861 2,526 363 2,889 A7D 25 3 28 B206B3 19 2 21 Aircraft Type No. Day Operations No. Night Operations Total Operations B206L 4 0 4 B212 5 1 6 B407 1 0 1 B427 5 1 6 B429 6 0 6 BEC58P 239 34 273 C130 4 0 4 C141A 0 1 1 C17 17 1 18 C5A 4 17 21 CIT3 68 12 80 CL600 1,621 174 1,795 CL601 24,007 2,363 26,370 CNA172 50 4 54 CNA182 21 4 25 CNA206 48 8 56 CNA208 1,541 80 1,621 CNA20T 8 0 8 CNA441 415 46 461 CNA500 61 10 71 CNA510 443 53 496 CNA525C 659 78 737 CNA55B 466 77 543 CNA560E 712 45 757 CNA560U 99 18 117 CNA560XL 939 89 1,028 CNA680 618 43 661 CNA750 931 99 1,030 COMSEP 1 0 1 CRJ9‐ER 22,823 2,176 24,999 CRJ9‐LR 1,747 152 1,899 CVR580 31 373 404 DC1010 309 202 511 DC1030 89 68 157 DC3 1 0 1 DC86HK 1 0 1 DC93LW 2 2 4 DHC6 9 12 21 DHC8 1 0 1 DHC830 4,506 171 4,677 DO228 589 47 636 DO328 4 0 4 EC130 14 2 16 ECLIPSE500 49 5 54 EMB120 8 362 370 EMB145 242 22 264 Read the entire page →
From page 49... ... Appendix B – Data Modeled for Noise Predictions B-3 Aircraft Type No. Day Operations No. Night Operations Total Operations EMB14L 605 2 607 EMB170 15,370 1,322 16,692 EMB175 45,307 3,946 49,253 EMB190 180 12 192 F10062 1,382 161 1,543 FAL20 3 1 4 GASEPF 9 0 9 GASEPV 116 15 131 GII 1 1 2 GIIB 103 19 122 GIV 1,972 335 2,307 GV 2,586 461 3,047 H500D 9 2 11 HS748A 3 2 5 IA1125 215 36 251 LEAR25 8 0 8 LEAR35 1,734 226 1,960 MD11GE 1,454 1,188 2,642 MD11PW 818 680 1,498 MD82 175 31 206 MD83 1,219 134 1,353 MD9025 2 0 2 MD9028 0 1 1 MU3001 332 33 365 PA28 17 1 18 PA30 15 2 17 PA31 17 3 20 R22 65 3 68 R44 99 7 106 S70 20 5 25 S76 43 7 50 SA341G 19 0 19 SA355F 108 25 133 SA365N 10 0 10 SD330 8 1 9 UNK 6,112 1,389 7,501 Total 530,994 119,804 650,798 Read the entire page →
From page 50... ... Appendix B – Data Modeled for Noise Predictions B-4 Table B‐3. Runway Utilization Operation Runway Day Night School Day Arrival 06L 0% 10% 0% 06R 0% 8% 0% 07L 0% 2% 0% 07R 0% 1% 0% 24L 11% 8% 11% 24R 34% 23% 34% 25L 53% 46% 53% 25R 1% 2% 1% Total 100% 100% 100% Departure 06L 0% 0% 0% 06R 0% 0% 0% 07L 0% 1% 0% 07R 0% 0% 0% 24L 41% 21% 41% 24R 1% 0% 1% 25L 3% 5% 2% 25R 55% 72% 55% Total 100% 100% 100% Notes: Totals may not add exactly due to rounding. School day runway use percentages are provided for informational purposes. Read the entire page →

From page 46...

... Appendix B Data Modeled for Noise Predictions

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From page 47...

... Appendix B – Data Modeled for Noise Predictions B-1 The following appendix provides a summary of input data used to produce the modeled noise metrics presented in Chapter 4. HMMH has developed a preprocessor named RealContoursTM that converts radar flight tracks to Integrated Noise Model (INM) tracks, thereby modeling each and every radar flight as an INM flight track and producing daily contours, which are then averaged to provide annual noise metrics. RealContoursTM uses individual flight tracks taken directly from radar systems rather than relying on consolidated, representative flight track data. This provides the advantage of modeling each aircraft operation on the specific runway it actually used and at the actual time of day of the arrival or departure. RealContoursTM then sets up an INM study for each day using the INM standard data. Each day is then modeled in the INM and the results for each day combined and averaged to get the annual DNL contours. The RealContoursTM approach essentially eliminates the approximation associated with the use of a limited set of prototypical modeling tracks by applying the INM's modeling capabilities on a flight‐by‐flight basis for over 138,000 tracks. This methodology, including the use of RealContoursTM, has been used for a variety of other FAA‐funded and reviewed projects including NEM projects at a number of airports. Modeled data for runway ends entered into RealContours™ are presented in Table B‐1. Table B‐1. Runway Data Runway Latitude Longitude Elevation (ft. MSL)

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From page 48...

... Appendix B – Data Modeled for Noise Predictions B-2 Table B‐2. Operations by Aircraft Type Aircraft Type No. Day Operations No. Night Operations Total Operations 1900D 2,363 150 2,513 717200 16,252 1,197 17,449 727D17 1 0 1 727EM1 10 5 15 727EM2 88 4 92 727Q15 5 1 6 727Q9 4 0 4 737300 15,733 2,050 17,783 7373B2 966 125 1,091 737400 2,345 300 2,645 737500 34 12 46 737700 53,865 7,641 61,506 737800 94,904 25,573 120,477 737N17 11 7 18 747200 40 178 218 74720A 26 89 115 74720B 64 210 274 747400 4,465 2,708 7,173 7478 1,553 2,032 3,585 757300 6,533 2,161 8,694 757PW 16,168 5,608 21,776 757RR 6,747 1,644 8,391 767300 12,473 5,683 18,156 767400 54 21 75 767CF6 77 487 564 767JT9 43 727 770 777200 5,829 2,206 8,035 777300 1,125 216 1,341 7773ER 18,119 7,230 25,349 7878R 7,689 1,468 9,157 A109 61 2 63 A300‐622R 544 722 1,266 A300B4‐203 36 393 429 A310‐304 14 1 15 A319‐131 28,559 6,227 34,786 A320‐211 26,547 3,958 30,505 A320‐232 15,271 5,489 20,760 A321‐232 33,830 12,052 45,882 A330‐301 4,799 1,691 6,490 A330‐343 216 0 216 A340‐211 2,550 391 2,941 A340‐642 1,237 127 1,364 A380‐841 3,620 1,747 5,367 A380‐861 2,526 363 2,889 A7D 25 3 28 B206B3 19 2 21 Aircraft Type No. Day Operations No. Night Operations Total Operations B206L 4 0 4 B212 5 1 6 B407 1 0 1 B427 5 1 6 B429 6 0 6 BEC58P 239 34 273 C130 4 0 4 C141A 0 1 1 C17 17 1 18 C5A 4 17 21 CIT3 68 12 80 CL600 1,621 174 1,795 CL601 24,007 2,363 26,370 CNA172 50 4 54 CNA182 21 4 25 CNA206 48 8 56 CNA208 1,541 80 1,621 CNA20T 8 0 8 CNA441 415 46 461 CNA500 61 10 71 CNA510 443 53 496 CNA525C 659 78 737 CNA55B 466 77 543 CNA560E 712 45 757 CNA560U 99 18 117 CNA560XL 939 89 1,028 CNA680 618 43 661 CNA750 931 99 1,030 COMSEP 1 0 1 CRJ9‐ER 22,823 2,176 24,999 CRJ9‐LR 1,747 152 1,899 CVR580 31 373 404 DC1010 309 202 511 DC1030 89 68 157 DC3 1 0 1 DC86HK 1 0 1 DC93LW 2 2 4 DHC6 9 12 21 DHC8 1 0 1 DHC830 4,506 171 4,677 DO228 589 47 636 DO328 4 0 4 EC130 14 2 16 ECLIPSE500 49 5 54 EMB120 8 362 370 EMB145 242 22 264

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From page 49...

... Appendix B – Data Modeled for Noise Predictions B-3 Aircraft Type No. Day Operations No. Night Operations Total Operations EMB14L 605 2 607 EMB170 15,370 1,322 16,692 EMB175 45,307 3,946 49,253 EMB190 180 12 192 F10062 1,382 161 1,543 FAL20 3 1 4 GASEPF 9 0 9 GASEPV 116 15 131 GII 1 1 2 GIIB 103 19 122 GIV 1,972 335 2,307 GV 2,586 461 3,047 H500D 9 2 11 HS748A 3 2 5 IA1125 215 36 251 LEAR25 8 0 8 LEAR35 1,734 226 1,960 MD11GE 1,454 1,188 2,642 MD11PW 818 680 1,498 MD82 175 31 206 MD83 1,219 134 1,353 MD9025 2 0 2 MD9028 0 1 1 MU3001 332 33 365 PA28 17 1 18 PA30 15 2 17 PA31 17 3 20 R22 65 3 68 R44 99 7 106 S70 20 5 25 S76 43 7 50 SA341G 19 0 19 SA355F 108 25 133 SA365N 10 0 10 SD330 8 1 9 UNK 6,112 1,389 7,501 Total 530,994 119,804 650,798

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From page 50...

... Appendix B – Data Modeled for Noise Predictions B-4 Table B‐3. Runway Utilization Operation Runway Day Night School Day Arrival 06L 0% 10% 0% 06R 0% 8% 0% 07L 0% 2% 0% 07R 0% 1% 0% 24L 11% 8% 11% 24R 34% 23% 34% 25L 53% 46% 53% 25R 1% 2% 1% Total 100% 100% 100% Departure 06L 0% 0% 0% 06R 0% 0% 0% 07L 0% 1% 0% 07R 0% 0% 0% 24L 41% 21% 41% 24R 1% 0% 1% 25L 3% 5% 2% 25R 55% 72% 55% Total 100% 100% 100% Notes: Totals may not add exactly due to rounding. School day runway use percentages are provided for informational purposes.

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