Metropolitan Airports Commission (MAC)

Metropolitan Airports Commission (MAC) Minneapolis-St. Paul International Airport (MSP) Noise Oversight Committee (NOC) MAC General Office Building Lindbergh Conference Room 6040 28 th Avenue South Minneapolis, MN 55450 NOC Committee Members Jeffrey Hart Co-Chair (Delta Air Lines) Elizabeth Petschel Co-Chair (Mendota Heights City Council) John Bergman At-large Cities Representative (Apple Valley City Council) John Carlson (United Parcel Service) Adam Ryan (Delta Global Services) Karen Erazo (Sun Country Airlines) Cyndee Fields (Eagan City Council) Tom Fitzhenry (Richfield City Council) Ben McQuillan (MBAA) John Oleson (Bloomington City Council) John Quincy (Minneapolis City Council) Bill Underwood (Chief Pilot Delta Air Lines) MEETING AGENDA July 16, 2014 1:30 P.M. (Jeff Hart, Delta Air Lines, will be the acting Chairperson for the meeting) *Note: 1:00 to 1:30 Committee Agenda Review Session (NOC members only in the Coleman Conference Room) 1. In Memory of Tom Perillo, Delta Chief Pilot 2. 1:30 1:35 Review and Approval of the May 8, 2014 Meeting Minutes 3. 1:35 1:40 Operations Report Summary: April, May, June 2014 4. 1:40 2:05 Presentation: Aviation Innovations, Delta Air Lines 5. 2:05 2:15 Annual MSP Nighttime Operations Assessment 2012 2013 6. 2:15 2:35 MAC Noise And Operations Monitoring System (MACNOMS) Validation Study 7. 2: 35 2:50 Public Comment Period 8. 2:50 Adjourn Notice: MAC operated audio and video recording devices may be used at NOC meetings

ITEM 2 METROPLITAN AIRPORTS COMMISSION MSP NOISE OVERSIGHT COMMITTEE MEETING MINUTES Thursday, 8 May 2014, 1:30pm MAC General Offices Building Lindbergh Conference Room Call to Order A regularly-scheduled meeting of the MSP Noise Oversight Committee, having been duly called, was held Thursday, 8 May 2014, in the Lindbergh Conference Room at the Metropolitan Airports Commission General Offices. Chair Petschel called the meeting to order at 1:40pm. The following were in attendance: Representatives: K. Erazo, J. Oleson, J. Quincy, D. Miller, T. Christiansen, B. Underwood, J. Hart, E. Petschel, J. Carlson, T. Fitzhenry, J. Bergman Staff: L. Peilen, J. Hamiel, J. Lewis, J. Giesen, G. Warren, T. Anderson Others: D. Sloan Mendota Heights Airport Relations Commission; L. Grotz Edina; A. Such Edina; S. Nienhaus City of Burnsville; M. Doran Richfield; D. Boberg Bloomington; C. Carrino Edina; J. Lindahl City of Rosemount; K. Hagerman City of St. Paul; J. Miller City of Mendota Heights; S. Neal City of Edina; K. Aacker City of Edina; L. Kinney Minneapolis; L. Kaczke Sun Newspapers; J. Bennett City of Edina; P. Dmytrenko City of Richfield; B. Hoffman City of St. Louis Park; S. Devich City of Richfield; L. Olson City of Minneapolis 1. Review and Approval of the 19 March 2014 Meeting Minutes Representative Miller, Eagan, noted that a correction should be made to Item 7, paragraph 6, line 2 of the 19 March 2014 meeting minutes; the word Eagan should be changed to Edina. Ms. Joni Bennett, City of Edina, noted that a correction should be made to Item 7, paragraph 6, line 9 of the 19 March 2014 meeting minutes; the word just should be

MSP Noise Oversight Committee 8 May 2014 2 inserted between capture and the. She also noted that corrections should be made to Item 7, paragraph 6, line 10 of the 19 March 2014 meeting minutes; the words there aren t should be struck and replaced with all, and the words completely encircling should be struck and replaced with don t simply encircle. IT WAS MOVED BY REPRESENTATIVE HART AND SECONDED BY REPRESENTATIVE FITZHENRY TO APPROVE THE MINUTES OF THE 19 MARCH 2014 COMMITTEE MEETING AS AMENDED. The motion carried by unanimous vote. 2. Operations Summary Report Jennifer Lewis, MAC Environment Noise Program Office, said complaints in March 2014 were nearly double the number of complaints for March 2013. She said complaints about departures off of Runway 30L, departures off of Runway 17 and arrivals over Minneapolis to Runway 12R helped drive the increase in complaints. J. Lewis said that total aircraft operations were down approximately 2% in March 2014 compared to March 2013. She said there were 34,051 total air carrier jet operations in March 2014, which is an increase of approximately 2% over March 2013. She said 50% of air carrier jet operations were conducted by regional jets in March 2013. J. Lewis said there was an increase of approximately 9% in major air carrier passengers in March 2014 compared to March 2013, and an increase of approximately 2% in regional air carrier passengers in March 2014 compared to March 2013. J. Lewis said total nighttime (10:30pm 6:00am) operations in March 2014 increased approximately 4% compared to March 2013, and carrier jet nighttime (10:30pm 6:00am) operations in March 2014 increased approximately 10% compared to March 2013. She said that, in March 2014, Runway 30L had the highest percentage of use for nighttime (10:30pm-6:00am) arrival operations, with 41.4%, and Runway 12R had the seconded highest percentage of use with 25.2%. She said that, in March 2014, Runway 12R had the highest percentage of use for nighttime (10:30pm-6:00am) departure operations, with 31.2%, and Runway 30L had the second highest percentage of use with 30.1%. J. Lewis said there was 99.8% compliance with the Runway 17 Carrier Jet Departure Procedure in March 2014. J. Lewis said that 94.5% of the Runways 12L and 12R carrier jet departures remained in the Eagan-Mendota Heights Departure Corridor in March 2014.

MSP Noise Oversight Committee 8 May 2014 3 J. Lewis said that 53% of nighttime (11:00pm-6:00am) carrier jet departures complied with the Crossing-in-the-Corridor Procedure, and that 28% of daytime (6:00am- 11:00pm) carrier jet departures complied with the Crossing-in-the-Corridor Procedure in March 2014. 3. Presentation: Sound Level Meter Measurement, Mr. Ken Cox, Product Manager, Larson Davis Ken Cox, Product Manager for Larson Davis, gave an overview presentation of sound level meter measurement. The Metropolitan Airports Commission s noise monitoring equipment is comprised of Larson Davis products. Highlights of the presentation included: Noise is any unwanted sound that we experience; noise sources vary Sound propagates in a wave form, and the fundamental principles that apply to other waves apply to sound Wavelength is the distance between peaks in a sound wave Frequency is related to the wavelength and speed of a sound wave Sound is composed of different frequencies; how a frequency interacts with the human ear and the environment is an important part of how sound and noise are perceived Air has an effect on sound waves by bending them and focusing their energy/pressure in different ways; temperature (high and low), wind, clouds and shielding provided by structures affect how sound is perceived on the ground Wind speed is not the same at all altitudes; generally, wind is slower the closer it is to the ground Wind speed and attenuation of air have effects on how sound propagates Temperature decreases bend sound down, temperature inversions bend sound upwards Entities monitor noise for many reasons, including improving community relationships, demonstrating organizational commitment and to collect data to support conclusions Standards establish quality thresholds, promote safety and reliability, support government policies and promote interoperability In the US, sound measurement industry standards are overseen by ANSI and administered by the Acoustical Society of America IEC international standards have recently been adopted by ANSI In a process known as pattern approval, sound level meter equipment is submitted to an independent laboratory for evaluation and certification to demonstrate compliance

MSP Noise Oversight Committee 8 May 2014 4 The equipment used by the MAC has been pattern approved by the French national lab, the German national lab and the Austrian national lab Larson Davis follows the process of legal metrology the application of legal requirements to measurements and measuring instruments for its products Representative Quincy, Minneapolis, asked if there is a way to measure or discern the loudness of a noise event. Cox said that is not necessarily his area of expertise, but that there are different algorithms for measuring loudness, each with their pros and cons. He said that individuals each experience and discern sound and noise differently, which complicates how loudness is discerned. He said he would be happy to send Quincy information for contacting people who are experts in the algorithms for measuring loudness. Quincy noted that others have said that loudness is difficult to measure. He asked what the effect is of distance on aircraft noise. Cox said that, generally, noise is quieter the further away the point source is. Representative Oleson, Bloomington, said it was his understanding that the MAC s noise monitoring equipment is rated to pick up sound the human ear could detect up to two miles distant. Cox said he is not sure what the two mile reference is, but that Larson Davis equipment is designed to measure sound pressure down to 20 db, which is typically well below ambient community noise. He said a sound meter s ability to detect that depends on what other sound sources are present and what the atmospheric effects are at the time. Chair Petschel, Mendota Heights, said the majority of complaints received a few winters ago concerned backwash sound off the ends of runways at MSP. She noted that there was very little snow cover that winter, and she asked if snow cover has anything to do with how sound is propagated over land. Cox said it does, that snow tends to absorb sound and reflect less sound than a hard surface. 4. Noise Monitoring Study West and Northwest of MSP: Fall 2014 John Nelson, Technical Advisor, presented a proposal for conducting a noise monitoring study west and northwest of MSP in fall 2014. He noted that the recommended study elements are: The noise monitoring will be focused on assessing existing aircraft noise levels The noise monitoring will be conducted for a period of two weeks in the fall of 2014 The monitoring will be limited to three locations in the area bound by I-494 on the south, Xerxes Avenue on the east from the intersection of I-494 and Xerxes Avenue extending in a straight line north to I-394, I-394 on the north, and Trunk Highway 169 on the west Two of the monitoring locations will be in the City of Edina and one will be located in the City of St. Louis Park The specific location of the monitors shall be determined by the respective cities, in consultation with MAC staff

MSP Noise Oversight Committee 8 May 2014 5 No monitor may be located within two miles of another permanent noise monitor The final report is due by December 1, 2014 Representative Hart, Delta Air Lines, asked what the cost would be for the study. Nelson estimated it would be $3,000 $10,000 in staff labor and time to conduct the study and complete the report. He noted the cost would be incurred by the MAC. Chair Petschel, Mendota Heights, noted that the Committee has not considered such an action previously and asked if doing such a study was unusual for the MAC. Nelson said it is not, that a noise monitoring study is conducted each year for the St. Paul Downtown Airport. Hart asked if a noise study would need to be conducted periodically in Edina and St. Louis Park to show trends. Nelson said that the purpose of the study proposed today is to establish current conditions, or baseline, conditions. He said that if warranted, it may be possible to conduct the study again in the future. Representative Fitzhenry, Richfield, said he is confident the noise monitors used for such a study will provide measurements consistent with measurements that would be provided by permanent RMTs. He said he is interested in seeing the ambient community noise levels that will be measured in the study, and asked if it is possible to measure ambient noise levels for each community. Petschel said the Mendota Heights City Administrator visited RMT 23 and the ambient noise recorded was between 40-50 db, without any aircraft noise present. Representative Quincy, Minneapolis, said he is supportive of the proposed study and appreciates MAC staff s willingness to conduct it. He asked if there is predictable noise that is expected to be shown in the study; if placing mobile monitors within two miles of an existing RMT would provide the ability to extrapolate noise measurements at other locations in the communities around the airport. Chad Leqve, MAC Director of Environment, said the two-mile area refers, in some cases, to an area of influence around an RMT, which is not a definitive monitoring area around an RMT. He said the two-mile area represents an assessment area the system of an RMT will look within two miles of the RMT for an aircraft overflight to correlate to a recorded noise event. Leqve said it is not safe to assume that mobile noise monitor data at one location can be extrapolated to other locations. Representative Oleson, Bloomington, commented that today s discussion demonstrates that determining noise is not just a scientific endeavor but that doing so takes into account an irritation factor. Petschel agreed, saying noise is also personal and emotional for many people. IT WAS MOVED BY REPRESENTATIVE BERGMAN, AND SECONDED BY REPRESENTATIVE CARLSON, TO DIRECT THE MAC NOISE PROGRAM OFFICE STAFF TO CONDUCT THE NOISE MONITORING STUDY DETAILED ABOVE AND AMENDED TO REMOVE THE SIXTH BULLET POINT, NO MONITOR MAY BE LOCATED WITHIN TWO MILES OF ANOTHER PERMANENT NOISE MONITOR, IN THE CITIES OF ST. LOUIS PARK AND EDINA. THE NOISE MONITORING

MSP Noise Oversight Committee 8 May 2014 6 REPORT SHALL BE COMPLETED BY DECEMBER 1, 2014 AND PROVIDED TO THE NOISE OVERSIGHT COMMITTEE AND THE PARTICIPATING CITIES. 5. Runway Use System Study John Nelson, Technical Advisor, noted that the Runway Use System (RUS) for MSP is intended to reduce noise impacts in densely-developed areas to the west and northwest of the airport. He said the RUS gives first priority to departure and arrival operations over open space, the Minnesota River, wetlands and noisecompatible commercial and industrial areas located to the south and southeast of MSP. He noted that air traffic control at MSP is solely the responsibility of the FAA, and that the MAC does not control aircraft. Nelson said that during a north flow configuration at MSP Air Traffic Control uses Runways 30R and 30L for departures, and uses Runways 30R, 30L and 35 for arrivals. He said that during a south flow configuration, Runways 12R, 12L and 17 are used for departures and Runways 12R and 12L are used for arrivals. Nelson said the existing RUS has been in place since 2005. Departure preferences under the RUS, in order of preference, are: Runways 12L and 12R, Runway 17, either Runway 22 or 04, and Runways 30L and 30R. He said arrival preferences, in order of preference, are: Runways 30L and 30R, Runway 35, either Runway 22 or 04, and Runways 12L and 12R. Nelson noted that there are low-, medium-, and high-air traffic demand periods, with arrival and departure banks or pushes, at MSP which have an impact on when the RUS can be utilized. He said wind pattern data for MSP for the past four decades correlate to the northwest-southeast layout of the airport s parallel runways. He noted that winds can vary significantly, however, by month. In April 2012 prevailing winds at MSP were out of the southeast, but in April 2013 the prevailing winds were out of the northwest. Nelson said that for the period 2012-2013, Runway 30R was used for approximately 30% of total nighttime departures, Runway 30L was used for 22%, Runway 12L was used for 19%, and Runway 30R was used for 14%. He said that, for the same period, Runway 30L was used for approximately 38% of total nighttime arrivals, Runway 12R was used for 30%, Runway 30R was used for 17%, and Runway 12L was used for 13%. Representative Quincy, Minneapolis, asked why operating in a north flow is more efficient. Nelson said efficiency has to do with the safe and orderly movement of aircraft on the ground and in the airspace. During periods of high-traffic demand, the north flow works best because three runways can be used for arrival operations and priority is given to landing aircraft over departing aircraft. Quincy asked if it s possible to quantify the difference in efficiency between the north and south flow. He

MSP Noise Oversight Committee 8 May 2014 7 noted that, on page 11 of the RUS Study May 2014, it says other runway configurations may be selected when tail wind speed is greater than 7 knots, but that the 7 knots is not a hard limit; Quincy asked what would be a hard limit. Nelson said Air Traffic Control Tower personnel indicated there is a range of conditions that compromise safety, including aircraft type, performance, load weight, wind direction, etc., which is why 7 knots is not a hard limit. Representative Hart, Delta Air Lines, said that, in effect, the airport is arranged for use by the most conservative pilot, because the pilot must be comfortable with the conditions; some may use a 7 knot tail wind, some may not. Representative Underwood, Delta Air Lines, noted that the 7 knot restriction at MSP is predominantly for arrival operations on Runway 35. Representative Miller, Eagan, noted that Figure 13 of the RUS Study May 2014 depicts the issue Eagan experiences, which is not the hours when the RUS is utilized but the daytime hours when it is not. She said residents see the RUS listing Runways 12R and 12L as preferred, but that the figure in the study shows Runway 17 being utilized 25% of the time for departures, as compared to Runway 12R being utilized 7%. Chair Petschel, Mendota Heights, said Mendota Heights is taking many more daytime operations than the Runway 17 EIS indicated. Miller said she would like feedback from the FAA on the issue, and Quincy and Petschel supported that request. Representative Bergman, At-large Representative, said he would like the FAA to look into whether or not Runway 17/35 will be used more if/when Terminal 2-Humphrey is expanded. Nelson said he will seek clarification on the issues from the Air Traffic Control Tower. Bergman noted that the arrival and departure banks at MSP are much tighter than they used to be. 6. Review of Runway 35 River Visual Approach Procedure John Nelson, Technical Advisor, reminded Committee members that review of a Runway 35 River Visual Approach Procedure is an item on the 2014 Work Plan. He noted that the Performance-Based Navigation Standard Terminal Arrival Routes by the FAA for implementation at MSP do not include the Runway 35 River Visual Approach Procedure. Chair Petschel, Mendota Heights, asked if the procedure will be in the Committee s 2015 Work Plan. Nelson said that would be at the Committee s pleasure. 7. Second Quarter 2014 Public Input Meeting Summary John Nelson, Technical Advisor, said there were 11 attendees at the second quarter 2014 Public Input Meeting, and that three people spoke on the record at the meeting. He said questions and concerns raised at the meeting included: Routing aircraft arrivals over non-residential land uses (Highway 77) Increased use of Runway 30L for departures to the northwest and west of MSP

MSP Noise Oversight Committee 8 May 2014 8 Concern that the Remote Monitoring Towers located to the northwest and west of MSP do not measure noise in communities further west of MSP The next Public Input Meeting will be held at 7:00pm on Tuesday, 29 July 2014 at the Mendota Heights City Hall. 8. Public Comment Period There were no public comments. 9. Item Not on the Agenda Chair Petschel, Mendota Heights, requested MAC staff look into the possible reasons for the increase in noise contour lobe adjacent to lakes in Minneapolis. The Committee expressed consensus on that request. John Nelson, Technical Advisor, said staff will prepare a response. The next meeting of the NOC is scheduled for Wednesday, 16 July 2014. The meeting adjourned at 3:14pm. Respectfully Submitted, Christene Sirois Kron, Recording Secretary

ITEM 3 MEMORANDUM TO: MSP Noise Oversight Committee (NOC) FROM: John Nelson, Manager Noise, Environment and Planning SUBJECT: CONTENT OF OPERATIONS REPORT SUMMARY DATE: June 16, 2014 Each month of the year the Metropolitan Airports Commission (MAC) produces a Technical Advisor s Report for the Noise Oversight Committee (NOC). This report provides maps, tables, and charts that examine runway use, departures and arrivals, and noise levels associated with aircraft operations at Minneapolis-St. Paul International Airport (MSP). The detailed content of a typical Monthly Technical Advisor s Report is provided below: 1) Complaint Data a) Number of Complaints i) Type (noise, engine run-up, low altitude, etc.), time of day/night, and complaint city of origin listing. b) Noise Complaint Map i) Showing location and number of complaints. 2) Runway Use a) FAA Available Time for Runway Usage i) Showing the airport layout and hours per month (all hours and nighttime hours) that each runway end met FAA Aviation Performance Metrics. b) MSP All Operations Runway Usage i) Showing the airport layout and the percentage of monthly flights for each runway. c) MSP Carrier Jet Operations Runway Usage i) Showing the airport layout and percentage of monthly flights by the air carriers. d) MSP Carrier Jet Fleet Composition i) Table showing type of aircraft, number of monthly operations at MSP, percentage of operations for each aircraft type and FAR Part 36 Take-Off Noise Levels. 3) Nighttime Runway Use (10:30 p.m. to 6:00 a.m.) a) MSP All Operations Nighttime Runway Usage i) Showing the airport layout and the percentage of use of each runway at night. b) MSP Carrier Jet Operations Nighttime Runway Usage i) Showing the airport layout and percentage of nighttime flights by the air carriers. c) MSP Scheduled Nighttime Operators i) Tables and a chart showing the names of the air carriers, number of operations per carrier and time of night of flights, including the schedule of nighttime jet operations. d) MSP Top 15 Nighttime Operators by Type and Stage Mix i) Tables and a chart the aircraft type (A320, MD 90, etc.), stage mix (Stage 3, hush-kitted, etc.), and type of aircraft used by the air carriers by time of night. 4) Airport Noise and Operations Monitoring System a) Flight Tracks i) A series of maps showing the density of weekly arrivals and departures and weekly flight tracks during the nighttime for each runway.

b) MSP MACNOMS Remote Monitoring Tower Site Locations Map i) A map showing the locations of each of the 39 Remote Monitoring Towers (RMT). c) Time Above db Threshold for MSP Arrival/Departure-Related Noise Events Tables showing the address location of each RMT and the amount of time for the month that each RMT recorded jet aircraft noise arrivals and departures events >=65dB, >= 80dB, >= 90dB and => 100 db. d) MSP Arrival/Departure-Related Noise Events i) Tables showing the count of jet aircraft arrival and departure events >=65dB, >= 80dB, >= 90dB and => 100 db. e) MSP Top Ten Aircraft Noise Events per RMT i) Tables showing the flight number, aircraft type, runway and L MAX (db). f) Analysis of Daily and Monthly Aircraft Noise Events DNL At the July 16, 2014 NOC meeting, MAC staff will provide an update on the Technical Advisor s Report for April, May, and June, 2014.

ITEM 4 MEMORANDUM TO: MSP Noise Oversight Committee (NOC) FROM: John Nelson, Manager Noise, Environment and Planning SUBJECT: Guest Speaker, Delta Air Lines DATE: June 17, 2014 At the July 16, 2014 Noise Oversight Committee meeting, Delta Air Lines will provide a presentation discussing Aviation Innovations.

ITEM 5 MEMORANDUM TO: MSP Noise Oversight Committee (NOC) FROM: Dana Nelson, Assistant Manager Noise, Environment and Planning SUBJECT: Annual Nighttime Operations Assessment DATE: June 17, 2014 The 2014 NOC Work Plan includes a review of the nighttime operations at Minneapolis-St. Paul International Airport (MSP). MAC staff has prepared the attached Annual Nighttime Operations Assessment comparing 2012 and 2013. This report is prepared annually to analyze trends in scheduled and actual nighttime operations at MSP. MAC staff will provide a briefing of the attached analysis at the July 16, 2014 NOC meeting.

Annual MSP Nighttime Operations Assessment 2012-2013 Metropolitan Airports Commission Noise Programs Office July 2014

Average Daily Nighttime Operations 10:30pm - 6:00am 80 75 73.2 72.6 70 67.9 Average Daily Operations 65 60 55 53.2 65.3 56.4 50 45 40 48.6 46.2 44.7 43.5 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Source: MACNOMS flight tracking data 1

Average Daily INM Nighttime Operations 10 pm - 7 am Average Daily 2007 Forecast 160 150 Average Daily Operations 140 130 120 116.3 127.1 127.2 131.5 127.1 110 107.8 107.2 100 99.1 98.2 94.5 90 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Source: MACNOMS flight tracking data 2

MSP Nighttime Runway Usage Summary of All Operations 10:30 pm to 6:00 am 2013 2012 MSP Runway Use Average Daily Operations Diagram MSP Runway Use Percentage Diagram RWY Arr/Dep Overflight Area Count of all Night Ops 3 2013 2012 Average Daily Night Ops Percent Count of all Night Ops Average Daily Night Ops Percent 4 Arr So. Richfield/Bloomington 4 0 0% 1 0 0% 12L Arr So. Minneapolis/No. Richfield 1706 4.7 13.3% 1377 3.8 11.6% 12R Arr So. Minneapolis/No. Richfield 3608 9.9 28% 3814 10.4 32% 17 Arr So. Minneapolis 12 0 0.1% 19 0.1 0.2% 22 Arr St. Paul/Highland Park 4 0 0% 12 0 0.1% 30L Arr Eagan/Mendota Heights 5149 14.1 40% 4515 12.3 37.9% 30R Arr Eagan/Mendota Heights 2163 5.9 16.8% 1962 5.4 16.5% 35 Arr Bloomington/Eagan 222 0.6 1.7% 206 0.6 1.7% Total Nighttime Arrivals 12868 35.3 100% 11906 32.5 100% 4 Dep St. Paul/Highland Park 6 0 0.1% 6 0 0.2% 12L Dep Eagan/Mendota Heights 708 1.9 17.7% 736 2 18.4% 12R Dep Eagan/Mendota Heights 1172 3.2 29.2% 1291 3.5 32.3% 17 Dep Bloomington/Eagan 471 1.3 11.7% 683 1.9 17.1% 22 Dep So. Richfield/Bloomington 2 0 0% 8 0 0.2% 30L Dep So. Minneapolis/No. Richfield 1052 2.9 26.2% 798 2.2 20% 30R Dep So. Minneapolis/No. Richfield 597 1.6 14.9% 473 1.3 11.8% 35 Dep So. Minneapolis 3 0 0.1% 0 0 0% Total Nighttime Departures 4011 11 100% 3995 10.9 100% Total Nighttime Operations 16879 46.2 15901 43.5 Sum of runway use percentage may not equal 100 due to rounding. Sum of average runway use breakdown may not equal total, due to rounding. Source: MACNOMS flight tracking data

MSP Nighttime Runway Usage Summary of Carrier Jet Operations 10:30 pm to 6:00 am 2013 2012 MSP Runway Use Average Daily Operations Diagram MSP Runway Use Percentage Diagram RWY Arr/Dep Overflight Area Count of Carrier Night Ops 4 2013 2012 Average Daily Night Ops Percent Count of Carrier Night Ops Average Daily Night Ops Percent 4 Arr So. Richfield/Bloomington 2 0 0% 0 0 0% 12L Arr So. Minneapolis/No. Richfield 1579 4.3 13.6% 1289 3.5 11.7% 12R Arr So. Minneapolis/No. Richfield 3250 8.9 28.1% 3549 9.7 32.3% 17 Arr So. Minneapolis 12 0 0.1% 16 0 0.1% 22 Arr St. Paul/Highland Park 2 0 0% 7 0 0.1% 30L Arr Eagan/Mendota Heights 4563 12.5 39.4% 4104 11.2 37.4% 30R Arr Eagan/Mendota Heights 1963 5.4 17% 1824 5 16.6% 35 Arr Bloomington/Eagan 198 0.5 1.7% 187 0.5 1.7% Total Nighttime Carrier Jet Arrivals 11569 31.7 100% 10789 29.5 100% 4 Dep St. Paul/Highland Park 3 0 0.1% 3 0 0.1% 12L Dep Eagan/Mendota Heights 657 1.8 18.7% 685 1.9 19.1% 12R Dep Eagan/Mendota Heights 979 2.7 27.9% 1134 3.1 31.6% 17 Dep Bloomington/Eagan 417 1.1 11.9% 634 1.7 17.7% 22 Dep So. Richfield/Bloomington 2 0 0.1% 3 0 0.1% 30L Dep So. Minneapolis/No. Richfield 877 2.4 25% 687 1.9 19.1% 30R Dep So. Minneapolis/No. Richfield 568 1.6 16.2% 446 1.2 12.4% 35 Dep So. Minneapolis 2 0 0.1% 0 0 0% Total Nighttime Carrier Jet Departures 3505 9.6 100% 3592 9.8 100% Total Nighttime Carrier Jet Operations 15074 41.3 14381 39.3 Sum of runway use percentage may not equal 100 due to rounding. Sum of average runway use breakdown may not equal total, due to rounding. Source: MACNOMS flight tracking data

INM Nighttime Runway Usage Summary of All Operations INM Nighttime Hours 10:00 pm to 7:00 am 2013 2012 MSP Runway Use Average Daily Operations Diagram MSP Runway Use Percentage Diagram RWY Arr/Dep Overflight Area Count of INM Night Ops 5 2013 2012 Average Daily Night Ops Percent Count of INM Night Ops Average Daily Night Ops Percent 4 Arr So. Richfield/Bloomington 4 0 0% 1 0 0% 12L Arr So. Minneapolis/No. Richfield 2720 7.5 14.4% 2503 6.8 14.2% 12R Arr So. Minneapolis/No. Richfield 4941 13.5 26.2% 5176 14.1 29.3% 17 Arr So. Minneapolis 12 0 0.1% 19 0.1 0.1% 22 Arr St. Paul/Highland Park 4 0 0% 12 0 0.1% 30L Arr Eagan/Mendota Heights 6847 18.8 36.4% 5981 16.3 33.9% 30R Arr Eagan/Mendota Heights 3852 10.6 20.5% 3521 9.6 20% 35 Arr Bloomington/Eagan 454 1.2 2.4% 426 1.2 2.4% Total INM Nighttime Arrivals 18834 51.6 100% 17639 48.2 100% 4 Dep St. Paul/Highland Park 47 0.1 0.3% 22 0.1 0.1% 12L Dep Eagan/Mendota Heights 3273 9 19.2% 4032 11 21.7% 12R Dep Eagan/Mendota Heights 4381 12 25.8% 5026 13.7 27% 17 Dep Bloomington/Eagan 2751 7.5 16.2% 3316 9.1 17.8% 22 Dep So. Richfield/Bloomington 7 0 0% 11 0 0.1% 30L Dep So. Minneapolis/No. Richfield 4001 11 23.5% 3477 9.5 18.7% 30R Dep So. Minneapolis/No. Richfield 2545 7 15% 2723 7.4 14.6% 35 Dep So. Minneapolis 3 0 0% 0 0 0% Total INM Nighttime Departures 17008 46.6 100% 18607 50.9 100% Total INM Nighttime Operations 35842 98.2 36246 99.1 Sum of runway use percentage may not equal 100 due to rounding. Sum of average runway use breakdown may not equal total, due to rounding. Source: MACNOMS flight tracking data

2013 Total Nighttime Carrier Jet Operations by Hour Hour Total 2230 3568 2300 4471 0000 1567 0100 587 0200 220 0300 176 0400 770 0500 3715 Total 15074 The top 15 nighttime operators represent 94.3% of total nighttime carrier jet operations in 2013. 2013 Top 15 Actual Nighttime Carrier Jet Operators by Type 10:30 pm to 6:00 am Airline ID Stage Type Count Airtran TRS 3 B717 322 Airtran TRS 3 B7377 1 America West AWE 3 A319 286 America West AWE 3 A320 300 America West AWE 3 A321 549 American AAL 3 B738 169 American AAL 3 MD80 408 Atlantic Southeast ASQ 3 CRJ 1 Atlantic Southeast ASQ 3 CRJ7 68 Atlantic Southeast ASQ 3 CRJ9 15 Atlantic Southeast ASQ 3 E135 266 Atlantic Southeast ASQ 3 E145 96 Compass CPZ 3 E170 448 Delta DAL 3 A319 324 Delta DAL 3 A320 509 Delta DAL 3 A330 45 Delta DAL 3 B738 474 Delta DAL 3 B757 1403 Delta DAL 3 B763 199 Delta DAL 3 B764 64 Delta DAL 3 MD80 285 Delta DAL 3 MD90 833 Fedex FDX 3 A300 11 Fedex FDX 3 A310 9 Fedex FDX 3 B72Q 2 Fedex FDX 3 B757 27 Fedex FDX 3 DC10 105 Fedex FDX 3 MD11 319 Pinnacle FLG 3 B738 1 Pinnacle FLG 3 CRJ 263 Pinnacle FLG 3 CRJ2 104 Pinnacle FLG 3 CRJ7 1 Pinnacle FLG 3 CRJ9 223 Republic Airlines RPA 3 E170 264 Skywest Airlines SKW 3 CRJ 167 Skywest Airlines SKW 3 CRJ2 129 Skywest Airlines SKW 3 CRJ7 140 Skywest Airlines SKW 3 CRJ9 154 Southwest SWA 3 B733 125 Southwest SWA 3 B7377 591 Southwest SWA 3 B738 11 Spirit NKS 3 A319 416 Spirit NKS 3 A320 412 Sun Country SCX 3 B7377 1099 Sun Country SCX 3 B738 1512 UPS UPS 3 A300 20 UPS UPS 3 B757 561 UPS UPS 3 B762 1 UPS UPS 3 B763 3 UPS UPS 3 MD11 214 United UAL 3 A319 85 United UAL 3 A320 84 United UAL 3 B735 2 United UAL 3 B7377 22 United UAL 3 B738 35 United UAL 3 B739 41 United UAL 3 B757 2 United UAL 3 CRJ7 1 Total 14221 2012 Total Nighttime Carrier Jet Operations by Hour Hour Total 2230 3447 2300 4451 0000 1377 0100 424 0200 189 0300 149 0400 777 0500 3754 Total 14568 The top 15 nighttime operators represent 95.3% of total nighttime carrier jet operations in 2012. Source: MACNOMS flight tracking data 2012 Top 15 Actual Nighttime Carrier Jet Operators by Type 10:30 pm to 6:00 am Airline ID Stage Type Count Airtran TRS 3 B717 537 Airtran TRS 3 B7377 49 America West AWE 3 A319 188 America West AWE 3 A320 493 America West AWE 3 A321 407 America West AWE 3 E190 2 American AAL 3 B738 192 American AAL 3 MD80 451 Atlantic Southeast ASQ 3 CRJ7 38 Atlantic Southeast ASQ 3 CRJ9 9 Atlantic Southeast ASQ 3 E135 45 Atlantic Southeast ASQ 3 E145 164 Compass CPZ 3 E170 542 Delta DAL 3 A319 315 Delta DAL 3 A320 697 Delta DAL 3 A330 25 Delta DAL 3 B738 784 Delta DAL 3 B744 3 Delta DAL 3 B757 1283 Delta DAL 3 B763 133 Delta DAL 3 B764 37 Delta DAL 3 DC9Q 10 Delta DAL 3 MD80 153 Delta DAL 3 MD90 750 FedEx FDX 3 A300 6 FedEx FDX 3 A310 1 FedEx FDX 3 B72Q 17 FedEx FDX 3 B757 1 FedEx FDX 3 DC10 210 FedEx FDX 3 MD11 217 Pinnacle FLG 3 CRJ 40 Pinnacle FLG 3 CRJ2 345 Pinnacle FLG 3 CRJ9 322 Shuttle America TCF 3 E170 306 Skywest Airlines SKW 3 CRJ 40 Skywest Airlines SKW 3 CRJ2 207 Skywest Airlines SKW 3 CRJ7 129 Skywest Airlines SKW 3 CRJ9 16 Southwest SWA 3 B733 93 Southwest SWA 3 B735 10 Southwest SWA 3 B7377 513 Spirit NKS 3 A319 393 Spirit NKS 3 A320 3 Sun Country SCX 3 B734 1 Sun Country SCX 3 B7377 887 Sun Country SCX 3 B738 1548 UPS UPS 3 A300 17 UPS UPS 3 B757 511 UPS UPS 3 MD11 203 United UAL 3 A319 122 United UAL 3 A320 258 United UAL 3 B735 80 United UAL 3 B7377 19 United UAL 3 B738 40 United UAL 3 B739 15 United UAL 3 B744 1 United UAL 3 B757 1 United UAL 3 B764 2 Total 13881 6

Nighttime Fleet Stage Mix for Top 15 Airlines - 2013 10:30 pm - 6:00 am Nighttime Fleet Stage Mix for Top 15 Airlines - 2012 10:30 pm - 6:00 am Stage 3 Stage 3 Manufactured Stage 3 Stage 3 Manufactured 5000 5000 4000 4000 3000 3000 2000 2000 1000 1000 0 0 AAL ASQ AWE CPZ DAL FDX FLG NKS RPA SCX SKW SWA TRS UAL UPS AAL ASQ AWE CPZ DAL FDX FLG NKS SCX SKW SWA TCF TRS UAL UPS Airline Stage 3 Stage 3 Manufactured Total AAL 0 577 577 ASQ 0 446 446 AWE 0 1135 1135 CPZ 0 448 448 DAL 0 4136 4136 FDX 2 471 473 FLG 0 592 592 NKS 0 828 828 RPA 0 264 264 SCX 0 2611 2611 SKW 0 590 590 SWA 0 727 727 TRS 0 323 323 UAL 0 272 272 UPS 0 799 799 Total 2 14219 14221 Airline Stage 3 Stage 3 Manufactured Total AAL 0 643 643 ASQ 0 256 256 AWE 0 1090 1090 CPZ 0 542 542 DAL 10 4180 4190 FDX 17 435 452 FLG 0 707 707 NKS 0 396 396 SCX 0 2436 2436 SKW 0 392 392 SWA 0 616 616 TCF 0 306 306 TRS 0 586 586 UAL 0 538 538 UPS 0 731 731 Total 27 13854 13881 Source: MACNOMS flight tracking data 7

Average Daily MSP Nighttime Operations 2012 Arrivals 2012 Departures 2013 Arrivals 2013 Departures 14.0 12.0 11.1 11.1 10.0 8.0 6.7 7.8 7.0 7.3 6.0 4.0 2.0 0.0 3.3 3.0 3.5 4.1 4.0 3.5 1.9 2.2 0.7 0.7 1.0 0.4 1.2 0.6 0.7 0.2 0.7 0.3 2.1 2.2 0.6 0.2 0.9 0.2 0.3 0.5 2230 2300 0000 0100 0200 0300 0400 0500 Hour Breakdown of 2013 Average Daily MSP Nighttime Operations Breakdown of 2012 Average Daily MSP Nighttime Operations 0500: 23.5% 2230: 23.2% 0500: 25.2% 2230: 22.9% 0400: 5.9% 0400: 5.4% 0300: 2.4% 0200: 2.0% 0100: 3.9% 0000: 10.4% 2300: 28.7% 0300: 1.9% 0200: 2.1% 0100: 3.2% 0000: 9.6% 2300: 29.8% Sum of average daily percentages may not equal 100 due to rounding. Sum of average daily operations may not equal total due to rounding. Source: MACNOMS flight tracking data 8

2013 Nighttime Scheduled Carrier Jet Operations 2012 Nighttime Scheduled Carrier Jet Operations 7000 25,784 Total Scheduled Operations Between 8:00 pm and 10:30 pm 7,466 Total Scheduled Operations During Nighttime Hours - 10:30 pm to 6:00 am 7000 29,159 Total Scheduled Operations Between 8:00 pm and 10:30 pm 7,802 Total Scheduled Operations During Nighttime Hours - 10:30 pm to 6:00 am 6000 6000 5000 5000 4000 4000 3000 3000 2000 2000 1000 1000 0 0 20:00:00 20:15:00 20:30:00 20:45:00 21:00:00 21:15:00 21:30:00 21:45:00 22:00:00 22:15:00 22:30:00 22:45:00 23:00:00 23:15:00 23:30:00 23:45:00 0:00:00 0:15:00 0:30:00 0:45:00 1:15:00 2:45:00 3:15:00 3:30:00 3:45:00 4:00:00 4:15:00 4:30:00 4:45:00 5:00:00 5:15:00 5:30:00 5:45:00 20:00:00 20:15:00 20:30:00 20:45:00 21:00:00 21:15:00 21:30:00 21:45:00 22:00:00 22:15:00 22:30:00 22:45:00 23:00:00 23:15:00 23:30:00 23:45:00 0:00:00 0:15:00 0:30:00 0:45:00 1:00:00 1:15:00 2:15:00 3:15:00 3:45:00 4:00:00 4:15:00 4:30:00 4:45:00 5:00:00 5:15:00 5:30:00 5:45:00 2013 Scheduled Operations During Nighttime Hours 10:30 pm to 6:00 am Airline Stage 2 Stage 3 Stage 3 Manufactured Total Sun Country (SCX) 0 0 1453 1453 Delta (DAL) 0 0 1259 1259 Us Airways (USA) 0 0 1156 1156 UPS (UPS) 0 0 753 753 United (UAL) 0 0 620 620 Spirit (NKS) 0 0 589 589 American (AAL) 0 0 585 585 Fedex (FDX) 0 0 469 469 Southwest (SWA) 0 0 323 323 Airtran (TRS) 0 0 221 221 Frontier Airlines (FFT) 0 0 23 23 Asiana Airlines (AAR) 0 0 15 15 Total 0 0 7466 7466 Nighttime Hours 2012 Scheduled Operations During Nighttime Hours 10:30 pm to 6:00 am Airline Stage 2 Stage 3 Stage 3 Manufactured Total Delta (DAL) 0 2 1865 1867 Sun Country (SCX) 0 0 1316 1316 US Airways (USA) 0 0 862 862 UPS (UPS) 0 0 697 697 United (UAL) 0 0 605 605 American (AAL) 0 0 579 579 Airtran (TRS) 0 0 556 556 FedEx (FDX) 0 12 459 471 Southwest (SWA) 0 0 446 446 Spirit Airlines (NKS) 0 0 286 286 Frontier Airlines (FFT) 0 0 69 69 Continental (COA) 0 0 48 48 Total 0 14 7788 7802 9

2013 Nighttime Scheduled vs Actual Carrier Jet Operations 10:30 pm - 6:00 am 6000 5000 4000 3000 2000 1000 0 Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual 22:30 23:00 00:00 01:00 02:00 03:00 04:00 05:00 AAL AAR COA DAL FDX FFT NKS SCX SWA TRS UAL UPS USA Other Airline Scheduled Stage 3 Actual Stage 3 Scheduled Manufactured Stage 3 Actual Manufactured Stage 3 Scheduled Total Actual Total Delta (DAL) 0 0 1259 4136 1259 4136 Sun Country (SCX) 0 0 1453 2611 1453 2611 Spirit Airlines (NKS) 0 0 589 828 589 828 UPS (UPS) 0 0 753 799 753 799 Southwest (SWA) 0 0 323 727 323 727 American (AAL) 0 0 585 577 585 577 FedEx (FDX) 0 2 469 471 469 473 Airtran (TRS) 0 0 221 323 221 323 United (UAL) 0 0 620 272 620 272 Frontier Airlines (FFT) 0 0 23 110 23 110 Continental (COA) 0 0 0 1 1 Asiana Airlines (AAR) 0 0 15 0 15 0 US Airways (USA) 0 0 1156 0 1156 0 Other 0 11 0 4206 0 4217 Total 0 13 7466 15061 7466 15074 Airlines in the Other category do not report schedules to the Official Airline Guide (OAG). Source: MACNOMS flight tracking data for actual counts; OAG, UPS and FedEx reporting for scheduled counts 10

2012 Nighttime Scheduled vs Actual Carrier Jet Operations 10:30 pm - 6:00 am 6000 5000 4000 3000 2000 1000 0 Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual Scheduled Actual 22:30 23:00 00:00 01:00 02:00 03:00 04:00 05:00 AAL COA DAL FDX FFT NKS SCX SWA TRS UAL UPS USA Other Airline Scheduled Stage 3 Actual Stage 3 Scheduled Manufactured Stage 3 Actual Manufactured Stage 3 Scheduled Total Actual Total Delta (DAL) 2 10 1865 4180 1867 4190 Sun Country (SCX) 0 0 1316 2436 1316 2436 UPS (UPS) 0 0 697 731 697 731 Airtran (TRS) 0 0 556 586 556 586 FedEx (FDX) 12 17 459 435 471 452 United (UAL) 0 0 605 538 605 538 Southwest (SWA) 0 0 446 616 446 616 American (AAL) 0 0 579 643 579 643 Frontier Airlines (FFT) 0 0 69 173 69 173 Continental (COA) 0 0 48 1 48 1 Spirit Airlines (NKS) 0 0 286 0 286 0 US Airways (USA) 0 0 862 0 862 0 Other 0 22 0 4180 0 4202 Total 14 49 7788 14519 7802 14568 Airlines in the Other category do not report schedules to the Official Airline Guide (OAG). Source: MACNOMS flight tracking data for actual counts; OAG, UPS and FedEx reporting for scheduled counts 11

ITEM 6 MEMORANDUM TO: MSP Noise Oversight Committee (NOC) FROM: John Nelson, Manager Noise, Environment and Planning SUBJECT: MAC Noise and Operations Monitoring System (MACNOMS) Validation Study DATE: June 30, 2014 At the July 16, 2014 meeting of the Noise Oversight Committee (NOC), MAC staff will present the MAC Noise and Operations Monitoring System (MACNOMS) Validation Study. Report Abstract The Metropolitan Airports Commission (MAC) owns and operates a Noise and Operations Monitoring network System (MACNOMS) that includes 39 Remote Monitoring Towers (RMTs) equipped with sound level meters/data-loggers, software that processes NextGen flight track data, and software that correlates noise events measured at the RMTs to actual flight tracks. This network is a complex system that is the backbone of the technology used by the MAC Noise Program Office for reports, maps, statistics, aircraft noise event tracking, the sound pressure level of events and the time and duration of an event. This study found strong correlation in noise-to-noise (0.9 db), noise-to-track (92.1%), and operation-to-operation (97.1%) for the field observations and the MACNOMS data outputs.

2014 Metropolitan Airports Commission Noise Program Office [MACNOMS VALIDATION STUDY] The Metropolitan Airports Commission (MAC) owns and operates a Noise and Operations Monitoring network System (MACNOMS) that includes 39 Remote Monitoring Towers (RMTs) equipped with sound level meters/dataloggers, software that processes NextGen flight track data, and software that correlates noise events measured at the RMTs to actual flight tracks. This network is a complex system that is the backbone of the technology used by the MAC Noise Program Office for reports, maps, statistics, aircraft noise event tracking, the sound pressure level of events and the time and duration of an event reading. This study found strong correlation in noise to noise (0.9 db), noise to track (92.1%), and operation to operation (97.1%) comparing field observations with the MACNOMS data outputs.

2014 MACNOMS Validation Study Table of Contents Introduction and Background 2 3 Purpose of the MACNOMS 3 System Architecture 3 Noise Data 3 4 Flight Track Data 4 Data Processing 4 Noise Data 4 5 Flight Track Data 6 Data Checks 6 MACNOMS Functionality 6 Data Publishing 7 Tools 7 Supplemental MACNOMS Technology, Software and Infrastructure 7 Previous MACNOMS Validation Reports and Results 8 9 Validation Methodology 9 Noise Data 2014 RMT Selection Criteria 9 10 Noise Data Field Testing Methods 10 12 Noise Data Sound Level Meter Event Detection 12 13 Noise Data L Max Comparison 13 14 Flight Tracks 14 Flight Tracks Airfield Observation Methods 15 16 MACNOMS/Observed Correlation Individual RMT Sites 5, 16, 23, 27, 28, 30, 33, 36, All RMTs 17 33 Discussion 34 36 Findings 36 Study Constraints and Limitations 37 Conclusions 37 38 List of Tables Table 1 Remote Monitoring Tower (RMT) Locations Used in this Study 10 Table 2 RMT Observation Log Details 10 11 Table 3 RMT Dates, Duration, Pre/Post Ambient, and Runway 12 Table 4 RMT and Portable Sound Level Meter Comparison 13 Table 5 Orange Ramp Field Observations Dates and Duration 15 Table 6 Count of Observations by Runway 16 Table 7 Observed Operations and MACNOMS Correlation 16 Table 8 Percentage of Noise Events and Observed Flight Correlated to the MACNOMS Data 38 List of Figures Figure 1 Larson Davis 831 Analyzer Event Detail 13 Figure 2 Wind Event Sound Pattern at RMT 30 34 Figure 3 A320 Arrival Event Sound Pattern at RMT 5 34 Figure 4 Correlation of Events With and Without Wind 35 Figure 5 Observations and Even Counts 36 Figure 6 Near Simultaneous Multiple Operations 36 1

Introduction and Background Periodically, the Metropolitan Airports Commission (MAC) conducts a validation analysis to ensure the data collected are representative of the conditions measured in the field. Prior to this report, the most recent validation study of the Metropolitan Airports Commission Noise and Operations System (MACNOMS) was done in 2006. Given community interest in airport noise issues, the Noise Oversight Committee (NOC) approved a 2014 Work Plan that included completing the MACNOMS Validation Study, as well as allowing for community representation and participation in the various steps and methods used for the analysis. In 1992, the MAC Noise and Satellite Programs Office installed one of the most sophisticated and comprehensive Airport Noise and Operations Monitoring Systems (ANOMS) of its kind. This system became the central element of an evolving noise and airspace analysis program that has been used extensively for reporting and analyzing aircraft operations and related noise levels around Minneapolis St. Paul International Airport (MSP). In 1998, the Metropolitan Aircraft Sound Abatement Council (MASAC) focused on increasing the noise monitoring coverage of the Airport Noise and Monitoring System (ANOMS), predicated on existing runway geometry, existing initial system site installations, associated aircraft operational patterns, and the utilization of increased spatial analysis capabilities. At that time, 24 Remote Monitoring Towers (RMTs) had been installed and were collecting data on all sides of MSP. Following a thorough and analytical process, the RMT Location Task Force established the location of additional new sites via the use of objective data sets, which enhanced the noise monitoring system s ability to measure aircraft overflight noise impacts in residential areas surrounding MSP. As a result of analysis conducted by the RMT Location Task Force, five new RMTs were added in 1999, bringing the total number of sites to 29. Three of the five new RMT sites were located north and west of MSP. In 2001, an additional 10 RMTs were added to coincide with development of a fourth runway (Runway 17/35) at MSP three in Bloomington, two in Burnsville, one in Apple Valley and four in Eagan. With the addition of the 10 RMTs the former ANOMS system reached its present total configuration of 39 towers. Limitations of ANOMS and newer technological options contributed to the MAC s interest in identifying new methods of collecting aircraft noise and flight tracking data. In 2009, the MAC moved from an off the shelf ANOMS product to downloading and processing flight tracks and noise data internally, which provided for increased reporting and analysis capabilities and an improved level of service to the community. The new MAC Noise and Operations Monitoring System (MACNOMS) was fully deployed by July 2009. At the time, MACNOMS was comprised of flight track data from a Multilateration (MLAT) system and 39 RMTs which provided noise data. 2

In November 2013, the MLAT flight tracking data source was replaced by a Next Gen data feed under a contract with the Exelis Corporation. The Next Gen data feed is the source for the flight tracking data currently used by MAC staff for noise to track matching, spatial analysis, monitoring aircraft operations counts, runway use percentages and to perform similarly detailed research and inquiries of the MACNOMS data. In brief, the use of Next Gen data represents the current state of the art with respect to flight tracking information provided by Exelis for activity within the National Airspace System. Purpose of the MACNOMS The MACNOMS is used continuously in the assessment of noise reduction measures and operational procedures at the airport. The components of MACNOMS allow for sophisticated noise and operations data analysis and provide an objective tool for assessing airspace use and noise impacts. Each month, MAC staff assesses and reports the collected noise and operations information in the monthly reports that are made available to the public. MAC staff uses the MACNOMS for such detailed analysis because of its capability to correlate data sets taken from two different sources. The Exelis data feed correlation functions match aircraft flight tracks with information specific to the operation, such as aircraft type and flight number. The MACNOMS system correlates this information with noise levels recorded by the Remote Monitoring Towers. The resulting information provides an accurate flight track displayed on a geo referenced map with specific flight information and the noise levels generated by the aircraft around the airport at the noise monitoring sites. The MACNOMS data are used to monitor compliance with approved noise abatement procedures at MSP as well as at the MAC s system of reliever airports. The MACNOMS was also used in the compatible land use analysis and the noise impact chapters of the MSP 2020 Improvements Environmental Assessment (EA)/Environmental Assessment Worksheet (EAW). System Architecture Noise Data The noise data associated with MSP are collected by a series of 39 RMTs that have been placed strategically around MSP. Each site consists of laboratory quality noise monitoring equipment manufactured by Larson Davis Incorporated (LD). The main components making up each RMT consist of a Type I LD 831 noise analyzer, an LD 426A12 preamplifier and an LD 2541 microphone. This equipment undergoes annual calibration and certification by an independent accredited laboratory. The analyzer in each RMT monitors noise levels continuously, utilizing slow response with A weighting as directed by the FAA s 14 CFR Part 150. The analyzer is set to record an event when the sound pressure level (SPL) reaches 65dBA and remains at or above this level for at least eight seconds. These recorded events are then later correlated with radar flight track data to 3

determine whether the noise source was a specific aircraft event or a community event. Each noise event and the associated information are stored in the individual RMT until it is transferred into the MACNOMS on a nightly basis. The analyzer also provides hourly and daily data. Each night, the MACNOMS dials in to each RMT automatically through a modem connection. Once a connection is established, various checks are performed to ensure the monitors are functioning adequately, and the data associated with the noise events are downloaded and imported into the MACNOMS. Information about the status of the RMTs is also downloaded and imported into the MACNOMS allowing MAC staff to perform daily checks to ensure the integrity of both the monitors and the noise data they collect. Flight Track Data The Exelis NextGen Data are a multi sensor based surveillance fused data feed available for the National Airspace System. The NextGen data feed contains Automatic Dependent Surveillance Broadcast (ADS B) data derived directly from the national ADS B Network owned by Exelis, and U.S. government sourced data including but not limited to: FAA en route and terminal secondary surveillance data, airport surface surveillance data from the FAA Airport Surface Detection Equipment Model X (ASDE X), Wide Area Multilateration (WAM) from the FAA deployed WAM systems, and flight plan data from the FAA host system. Data Processing Noise Data Noise data are processed in a number of ways, resulting in the calculation of metrics that indicate the community and aircraft generated noise levels in the vicinity of an RMT. However, before these calculations can be performed, noise events generated by aircraft must be distinguished from non aircraft events that are generated within the community. The function within the MACNOMS that makes this distinction possible is called noise to track matching. The noise to track function defines the source of noise events by analyzing the aircraft activity in the vicinity of an RMT at the time the event was recorded. These two variables, time and distance from the RMT, are crucial to defining the noise source accurately. The primary way in which the noise to track function matches a noise event with the noise source is by analyzing the time the event occurred. If an aircraft is operating in the vicinity of a RMT at the same time a noise event is generated, it is possible the aircraft could have been the source that generated the event. However, such a generalization would lead to noise events being attributed to aircraft operating at distances beyond the audible coverage area of an RMT. Therefore, parameters restricting the distance an aircraft can be from an RMT and still be considered to have caused the noise event must be defined. 4

Within the MACNOMS each RMT is assigned a coverage area that is a function of the capabilities of the monitor, the geometric nature of flight tracks in the area, and the geography of the surrounding land. This area is referred to as the Area of Influence, and is used in the filtering of aircraft operating at the same time a noise event is generated. The Area of Influence filter provides the noise to track function with the capability to determine whether an aircraft could be responsible for the noise that caused a noise event. In the event the noise source is determined to be an aircraft, the noise data recorded by the RMT are matched to that aircraft and calculated to determine noise values and metrics relative to aircraft operations. There are instances, however, when the noise data matched to the aircraft have been influenced by one or more other noise sources. Such instances occur when multiple aircraft are operating in the vicinity of an RMT and contributing to the same noise event, or when a community noise source is contributing to or causing a noise event when an aircraft is operating within an RMT s Area of Influence. Because scenarios such as the ones described above exist, parameters within the noise to track function and the RMTs are defined to minimize the probability that noise data are matched to an incorrect noise source. The simplest restriction that prevents the matching of incorrect data is that of the noise event parameter within the RMT itself. For a noise event to be considered a prospective aircraft noise event the level at a specific RMT site must reach 65 db and remain at or above 65 db for at least eight seconds. The significance of the 65 db threshold is that normal urban areas surrounding major airports such as MSP have community noise events that reach an L Max of 65 db regularly, affecting normal speech communication. As such, aircraft noise events do not begin to affect metropolitan urban life significantly below 65 db. The threshold provides a necessary function to filter erroneous community noise. The situation becomes more complicated, however, when a noise source does generate a noise event while one or more aircraft are flying through an RMT s Area of Influence. In the event that two aircraft are flying through the Area of Influence at the same time a noise event is generated, the noise to track function is programmed to refer to a static database 1 of predetermined aircraft noise values to determine which aircraft most likely generated the event. However, it is possible the noise source generating the event was not an aircraft, but rather a source in the community. When a noise event is generated from a source in the community and there are no aircraft operating in an RMT s Area of Influence, the noise data associated with the event are attributed to a source within the community. In some cases, when an aircraft is operating in the Area of Influence at the time of the community generated event, the noise data associated with the event can be attributed to the aircraft. 1 The database referred to contains average noise values of aircraft that have been determined and published under the auspices of Federal Aviation Regulation Part 36. 5

Flight Track Data Flight Track Data are the four dimensional positional information of an aircraft (X/Y/Z and a time value for where the point is along the track line). The Exelis Next Gen data feed used by the MACNOMS flight track data processing includes, enroute radar, terminal secondary surveillance data, Airport Surface Detection Equipment Model X (ASDE X), and Automatic Dependent Surveillance Broadcast (ADS B) data. The ASDE X data are a new feature of the Next Gen data and are used to track movements of aircraft and vehicles on the airport surface movement area and from aircraft transponders. The ADS B is a satellite based geographical positioning system (GPS) that is intended to replace radar based positioning systems within the National Airspace System in the future. Next Gen data used by the MACNOMS are considered near real time. There is a 20 minute delay of actual aircraft operations loaded into the data feed for public applications. The Next Gen data feed includes the unique flight identifier, a time stamp, a message type (flight start, amended, flight end), the flight ID number, the aircraft s call sign, aircraft type, latitude, longitude, altitude, heading, airspeed, secondary surveillance radar Mode3/A (aircraft within the range of the radar signal), the particular radar/satellite tracking source used, the aircraft category (unknown, light, small, large, heavy, rotorcraft or other), the filed flight route, the departure fix, and alerts (such as radio failure or emergency). The data coming from the Exelis NextGen data feed consist of the real time data feed and a nightly file download. The real time data are broadcast from external servers at Exelis over a secure connection fed into the database and displayed on the macnoise.com website FlightTracker application with a 20 minute delay. The nightly file download provides complete flight track data from the previous 24 hours, delivered through a secure file transfer protocol and imported into the MACNOMS database each morning. The flight tracks from the nightly data file are then correlated with noise data downloaded from the MAC s system of RMTs located in the communities surrounding MSP. Data Checks Following the nightly import of the aircraft noise data from the RMTs a check of the data completeness and accuracy is conducted by MAC staff. On occasion, an interruption of the RMT data collection due to hardware and connection outages can occur, as was the case in May 2014 when an RMT was struck by lightning and a phone modem had to be replaced. It is rare for RMT data to be unrecoverable, as each meter stores the noise data measured, which can be downloaded manually. 6

MACNOMS Functionality MACNOMS data are the backbone of many of the Noise Program Office s mission critical functions such as interactive flight tracking, RMT noise levels for a single flight track, and customized user defined data retrieval inquiries under the Reports on the Fly link at www.macnoise.com. The MACNOMS data can be queried to provide: counts of all aircraft and carrier jet operations by runway and runway percentage of use, nighttime counts of all aircraft and jet carrier operations by runway and runway percentage of use, aircraft type counts, aircraft noise events summaries by aircraft type, and the daily noise event summary for a specific RMT. Many of these inquiries can be retrieved from the MACNOMS data base going back to the year 2001. Data Publishing Other MACNOMS data processes tag aircraft events to specific airports and runways, record runway use, determine compliance with noise abatement procedures, and calculate noise impacts with various metrics such as Day Night Average Sound Level (DNL), Time Above, and Number of Events Above. The MACNOMS data and tools have proven to be valuable for investigating specific aircraft operations and associated noise. MAC Noise Program Office staff are able to analyze flight data and aircraft noise to identify trends, view activity for specific locations, research runway use and fleet mix information, and to conduct sophisticated modeling and analyses associated with environmental assessments, planning studies, and aircraft flight procedure monitoring and development. Many of the MACNOMS data described above are published in the Monthly Technical Advisor s Report, the Eagan Mendota Heights Corridor Report, the Runway 17 Departure Analysis Report and the Crossing in the Corridor Analysis. These reports are posted under the Tools and Reports drop down menu at www.macnoise.com. Tools MAC Noise Program Office staff are able to retrieve and investigate noise complaints, and track aircraft noise complaint trends through a specialized web based application called Aircraft Noise Complaint and Communications Record System (ANCCRS). ANCCRS provides MAC staff with a comprehensive suite of internally used noise complaint investigation tools. Complaint details and communication records are stored for each address recorded. The ANCCRS mapping function integrates spatial flight track and geographical complaint location information and displays weather, flight activity, aircraft noise events and documented aircraft maintenance run ups that occurred during the reported complaint date and time. ANCCRS will also display other complaint locations if there are any that were filed during the reported time period. ANCCRS uses the MACNOMS data as the primary source for these analytical, mapping, and technical outputs. 7

Supplemental MACNOMS Technology, Software, and Infrastructure The MACNOMS system incorporates a wide variety of software technology and applications in the processing of the RMT and Exelis Next Gen data. Programming languages include: Python, Structured Query Language (SQL), JavaScript, PHP, R Programming Language, Shell Script, JavaScript Object Notation (JSON), and Comma Separated Variables (CSV). Software includes: Apache Web Server, MapServer, GeoServer, ESRI ArcGIS, the CRON scheduling utility, Github, pgadmin, Putty, and NextGen (a series of related Python scripts developed by the MAC for processing data provided by Exelis). Additional computer infrastructure includes: Data Base Servers, Linux Operating Systems and a Storage Area Network. The technology, software, and infrastructure of the MACNOMS are supported by up to 10 computer servers. Previous MACNOMS Validation Reports and Results Periodically, the MACNOMS is tested to verify that it continues to meet a high standard of accuracy. The validation of the MACNOMS accuracy is prudent since it is relied upon daily for analysis of noise issues around the Twin Cities metropolitan area. Evaluating the accuracy of the data extracted from the MACNOMS requires evaluation of the accuracy of the data processing functions. To record and match the data associated with the MACNOMS noise to track function independently, MAC staff recorded noise events in close proximity to the RMTs. By working in the vicinity of an RMT with an independent noise monitor, staff was able to determine visually and aurally, and record, the sources that were creating the noise events. In the 2001 and 2004 studies, MAC staff spent several days at RMT sites around the MSP working with an independent noise monitor and recording visually and making an aural determination of the actual noise sources that were creating the noise events (both aircraft and community events). The data collected in the field were processed independently and compared to the actual data extracted from the ANOMS for the same time period to determine the accuracy of the ANOMS noise to track function and the validity of the calculated noise values and metrics. In addition, several days were spent in the Air Traffic Control Tower (ATCT) collecting independent data in order to analyze the aircraft flight track and specific information processing functions within the ANOMS. Staff utilized the vantage point of the air traffic control tower to record the approximate start or stop time of actual aircraft operations and the specific information of each aircraft operation (aircraft type, airline, runway, and arrival/departure). This information was then compared to actual aircraft specific information from the ANOMS to 8

determine the accuracy of the aircraft radar flight track data and the aircraft specific information processing functions within the ANOMS. In the summer of 2001, MAC staff collected both sets of data (RMT noise data and ATCT operations data) simultaneously over a three day period. Approximately 39.7 hours of monitoring was conducted in the ATCT, and approximately 48.2 hours of monitoring at the RMT sites was performed. During this study, over 13 different RMT sites were used in the community monitoring. In the summer of 2004, MAC staff collected the same data over a three day period. During that time approximately 36 hours of monitoring in the ATCT, and approximately 29 hours of monitoring at RMT sites was performed. Seven different RMT sites were used in the community monitoring. In 2005, MAC Noise Program Office staff decided to expand the scope of the ANOMS validation study to more thoroughly assess the accuracy of the data extracted from ANOMS and to identify any possible areas or situations that may need to be monitored, enhanced or further investigated. To accomplish this, the Noise Program Office employed a full time noise monitoring position for the months of June, July and August 2005. A total 218 hours of noise monitoring was conducted at the 39 RMT sites and a total of 82 hours of monitoring was conducted in the ATCT. The results for all three studies were similar. For the 2005 study, 95.9% of the observed operations from the ATCT correlated with ANOMS (flight track and specific information) and 94.3% of the total number of noise events observed at the RMT sites correlated with ANOMS (aircraft noise event information). For the 2004 study, 96.8% of the observed operations from the ATCT and 89.1% of the total number of noise events observed at the RMT sites correlated with ANOMS. In 2001, 97.8% of the observed operations from the ATCT and 90.9% of the total number of noise events observed at the RMT sites correlated with ANOMS. Validation Methodology Noise Data 2014 RMT Selection Criteria Due to limited staffing resources, MAC staff determined that, in field validation tests, not all of the 39 RMTs could be monitored. The following criteria were used to establish the list of candidate RMT sites: 1. The RMT location must be easily accessible and have sufficient space to accommodate MAC staff and a team of observers. 9

2. Where multiple RMTs exist in a community, selection should be based upon the frequency of events and the proximity of flight tracks, and the location should be subjected to departure operations, arrival operations, or both. Based on these criteria, the following eight RMT sites were included in this study: Table 1 RMT # Location 28 Richfield 6645 16th Ave. S. 27 Minneapolis Anthony School 5757 Irving Ave. S. 5 Minneapolis 12th Ave. & 58th St. 30 Bloomington 8715 River Ridge Rd. 23 Mendota Heights End of Kenndon Ave. 16 Eagan Avalon Ave. & Vilas Ln. 36 Apple Valley Briar Oaks & Scout Pond 33 Burnsville North River Hills Park Field Testing Methods Field monitoring was conducted at each individual RMT site to compile data for an Observation Log matrix as shown below. Table 2 Observation Log Details Event Date Start Time of Event End Time of Event LMAX Aircraft Type or Description of Community Noise Source Arrival or Departure Runway RMT Comments about the Event Observation Notes to include: Date of Observation Start Time of Monitoring Period 10

Stop Time of Monitoring Period RMT Arrival/Departure Temp (At Site) Relative Humidity (At Site) Wind Direction (At Site) Wind Speed (At Site) Meter Serial # Calibrator Serial # Pre Cal Check/Change Level Post Cal Check Level Pre Ambient Post Ambient Observer Names Upon completion of the field data collection, the field computer entries and the sound level meter data were downloaded into a software spreadsheet application for additional data comparison and analysis with the noise event and flight tracking data recorded independently by the MACNOMS for the same time period. For the purpose of comparing the noise data, two parameters were established. First, MAC staff recorded the L Max sound level of the flight as captured by the portable sound level meter (a Model LD 824 Type I) for comparison with the MACNOMS L Max sound level recorded by the sound level meter on the RMT tower (LD 831 Type I). Second, the portable sound level meter was programmed manually to recognize a noise signal greater than a threshold of 65 decibels lasting at a level greater than 63 decibels for eight consecutive seconds as a possible aircraft noise event. The second parameter is identical to the aircraft noise event programmed for the permanent sound level meters placed on the 39 RMTs. There are, however, community noise events such as loud vehicles that can generate noise events that meet the aircraft noise event threshold described in the second parameter. Therefore, matching the noise event to an aircraft track provides a secondary check that the noise event may have been caused by an aircraft. Table 3 provides the date, times, duration, and pre/post ambient sound levels during the field observation in 2014. 11

Table 3 Pre/Post Runway Date Start Stop Duration RMT A/D Ambient 4/7/2014 9:12:44 10:46:31 1:33:47 23 A 54/52 30R 4/7/2014 13:44:00 15:02:36 1:18:36 36 A 52/57 35 4/10/2014 12:55:09 14:59:01 2:03:52 30 A 64/54 35 4/11/2014 13:43:40 15:08:29 1:24:49 5 D 45/48 30L/R 4/14/2014 9:25:52 11:27:38 2:01:46 28 D 55/53 30L/R 4/15/2014 12:31:44 14:38:01 2:06:17 27 D 43/49 30L/R 4/15/2014 8:45:59 10:51:14 2:05:15 23 D 57/52 12L 4/15/2014 13:57:43 15:29:54 1:32:11 5 A 55/55 12R 4/17/2014 9:29:45 11:02:29 1:32:45 16 A 56/54 30L/R 4/21/2014 9:48:00 11:48:31 2:00:31 33 A 45/48 35 4/21/2014 13:33:56 15:03:40 1:29:44 30 A 54/58 35 4/22/2014 9:56:07 11:05:52 1:09:45 36 A 57/57 35 4/22/2014 12:23:14 14:30:35 2:07:21 27 D 45/48 30L/R Total Duration 22:26:37 Note: the pre ambient of 64 at RMT 30 on 4/10/14 was caused by high wind speeds during the observation period. Sound Level Meter Event Detection Transient noise events do not always begin or end abruptly. Both the LD 824 and the LD 831 sound level meters have a method to continue the measurement of an event as it is ending to avoid losing data and to eliminate multiple records for a single event. The portable sound level meter LD 824 logged an event when the sound pressure level exceeded 65 db and remained above 63 db for more than eight seconds. The event detection was defined by three basic parameters: a threshold level (65 db), a minimum duration (8 sec.), and hysteresis (2 db). The permanent sound level meter, LD 831, while using the same parameters for event counting, has an improved method of detection for event history. Rather than utilizing a hysteresis of the sound pressure level to define how an event ends, a user definable continuation period is employed. The continuation period defines how long the analyzer will wait after the threshold level is no longer exceeded to ensure that the sound pressure level does not re exceed the threshold level. The threshold and minimum duration parameters remain the same as the portable sound level meters. To recap, the new analyzers log an event when the sound pressure level exceeds 65 db and remains above 65 db for at least eight seconds. When the sound pressure level no longer exceeds the threshold the continuation period begins. If within that time the sound pressure 12

level re exceeds the threshold, then the event continues; if not it ends when the sound pressure level drops below 65 db. Figure 1 L Max Comparison The Maximum A Weighted Sound Level, L Max, measures the highest root mean square sound level that occurs during a single event in which sound level varies with time. The L Max metric can be used to describe a single aircraft noise event and is measured in decibels. During the field measurement data collection, the portable sound level meter L Max was captured after the sound level reached 65 decibels for eight seconds during an aircraft operation. These L Max levels were then compared to the sound level captured by the sound level meter on the RMT for the same event at the same time by querying the MACNOMS database. The results of the comparison are shown in Table 4. Table 4 RMT# Events Over Under AVE 5 61 1.5 1.8 0.8 16 30 1.1 0.8 0.5 23 36 3.8 1.4 1.1 27 15 2.1 1.5 1.1 28 17 3.4 1.5 1.0 30 11 1.7 1.3 0.6 36 27 1.4 2.3 1.0 Total 197 0.9 13

Note: The Over value represents the maximum variation when the portable sound level meter reading was above the RMT sound level reading for all of the events recorded at the specific RMT. The Under value represents the maximum variation when the portable sound level meter reading was below the RMT sound level reading for all of the events recorded at the specific RMT. The average (AVE) is the absolute value of both the Over and Under variations The close agreement in the L Max average levels is consistent with acoustical performance levels for laboratory grade Type I sound level meters. While it is rare for two sound level meters to give exactly identical readings when placed side by side and exposed to a variable noise source (such as an aircraft overflight), average agreement within 0.9 of a decibel is the result of the precision of the sound level meters, which are calibrated annually by the manufacturer and by MAC staff as needed. In addition, early every morning, each RMT performs an automated calibration check. This calibration check utilizes an electrostatic actuator mounted on the RMT s microphone to generate a precision level. This daily level is then checked against an established reference level to determine changes in the system s calibration, whether in the microphone, instrumentation, cabling or the electrostatic actuator itself. There was one event at RMT 23 for which the portable sound level meter and the RMT sound level meter varied by 3.8 decibels. A review of the field observation log during the events determined that community noise (a truck) was the cause of the measured variance. Similarly, there was one event at RMT 28 for which the portable sound level meter and the RMT sound level meter varied by 3.4 decibels. A review of the field observation log during the events determined that community noise (a motor vehicle braking) was the cause of the measured variance. These two events had the greatest variance of the 197 events examined. When community noise and aircraft noise are present simultaneously at an RMT, the L Max of the louder of the two sources is recorded in the MACNOMS. Therefore, there may be a small number of instances in the MACNOMS where the L Max attributed to the aircraft flight is slightly greater than that generated by the flight itself, due to the community noise that occurred at the same time. Flight Tracks Airfield operation observations took place at the MSP Orange Parking Ramp, located next Terminal 2 Humphrey one of the tallest structures on the MSP campus with a height of 979 feet above sea level. The top of the Orange Parking Ramp offers good sightlines to Runway 4/22, Runway 17/35 and Runway 30L/12R. Views of Runway 30R/12L are acceptable for the observation purposes of the 2014 MACNOMS Validation Study. 14

Airfield Observation Methods Observations were taken during normal MAC business hours on April 23 25, 2014 for a total of 8 hours and 29 minutes. Table 5 shows the documented dates and times of airfield operation observations. Table 5 Orange Ramp Field Observation Duration Summary Date Start Time Stop Time Duration 4/23/2014 10:12:20 11:33:11 1:20:51 4/23/2014 12:37:14 13:07:30 0:30:16 4/24/2014 12:22:21 13:48:42 1:26:21 4/24/2014 14:05:58 15:24:36 1:18:37 4/25/2014 10:03:54 11:54:08 1:50:14 4/25/2014 13:09:24 15:12:42 2:03:18 Total 8:29:37 MAC staff visually observed each aircraft operation and recorded the following information for each operation: date, time of operation, aircraft type, runway, arrival or departure. During the documented airfield operation observation periods there were a total of 649 operations: 283 arrivals and 366 departures. Table 6 shows the number of operations documented for each runway. 15

Table 6 Count of Observations by Runway Date 17 35 12L 12R 30L 30R Grand Total Arrivals 57 73 83 25 45 283 4/23/2014 25 33 58 4/24/2014 48 50 98 4/25/2014 57 25 45 127 Departures 104 61 5 118 78 366 4/23/2014 42 20 2 64 4/24/2014 62 41 3 106 4/25/2014 118 78 196 Grand 104 57 134 88 143 123 649 Total Note: There were no aircraft observations for Runway 4/22 during the observation period. The observed data were compared to actual data from the MACNOMS for the same period to determine the accuracy of the MACNOMS flight track information. Table 7 Date Number of Operations Observed Observations that matched MACNOMS Observations that did not match MACNOMS % correlation =observed/ MACNOMS 4/23/2014 122 118 4 96.7% 4/24/2014 204 199 5 97.5% 4/25/2014 323 313 10 96.9% Totals 649 630 19 97.1 % ave. Note: Several of the observations that did not match the MACNOMS were military flights that, generally, are not included in the Exelis Next Gen data feed. 16

MACNOMS/Observed Correlation The findings from the observed operations at each RMT site were compared to the noise data that were obtained from the MACNOMS for the same monitoring period. Each observed noise event was compared to the actual MACNOMS data for the same monitoring period to determine if the event correlated with the field observations made at the RMT sites. In addition, the findings also present the number of single noise events in the MACNOMS that were observed in the field to be created by multiple aircraft noise sources and/or observed to be created by both aircraft and community noise (e.g., loud truck driving by while an aircraft is flying over a RMT). This additional information helps to assess the overall noise environment and what type of activity (aircraft and community noise) may be occurring at each RMT site that is not attributed to an aircraft noise event in the MACNOMS. 17

RMT #5 12 th Avenue & 58 th Street, Minneapolis Aircraft operations correctly identified as aircraft events 58 Multiple aircraft operations correctly identified as aircraft events 4 Community sources correctly identified as community events 1 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 3 Aircraft operations incorrectly identified as community events 1 Community sources incorrectly identified as aircraft events 0 Wind noise incorrectly identified as aircraft events 0 Wind noise incorrectly identified as community events 0 All events 67 Correlation with wind events 94.0% Correlation without wind events 94.0% 18

RMT 5 Aircraft operations correctly identified as aircraft events 4 1 3 1 Multiple aircraft operations correctly identified as aircraft events Community sources correctly identified as community events Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft Aircraft operations incorrectly identified as community events Community sources incorrectly identified as aircraft events 58 Wind noise incorrectly identified as aircraft event Wind noise incorrectly identified as community event 19

RMT #16 Avalon Avenue & Vilas Lane, Eagan Aircraft operations correctly identified as aircraft events 30 Multiple aircraft operations correctly identified as aircraft events 0 Community sources correctly identified as community events 2 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 0 Aircraft operations incorrectly identified as community events 0 Community sources incorrectly identified as aircraft events 1 Wind noise incorrectly identified as aircraft events 0 Wind noise incorrectly identified as community events 0 All events 33 Correlation with wind events 97.0% Correlation without wind events 97.0% 20

RMT 16 2 1 Aircraft operations correctly identified as aircraft events Multiple aircraft operations correctly identified as aircraft events Community sources correctly identified as community events Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft Aircraft operations incorrectly identified as community events Community sources incorrectly identified as aircraft events 30 Wind noise incorrectly identified as aircraft event Wind noise incorrectly identified as community event 21

RMT #23 End of Kenndon Avenue, Mendota Heights Aircraft operations correctly identified as aircraft events 29 Multiple aircraft operations correctly identified as aircraft events 4 Community sources correctly identified as community events 3 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 1 Aircraft operations incorrectly identified as community events 1 Community sources incorrectly identified as aircraft events 1 Wind noise incorrectly identified as aircraft events 0 Wind noise incorrectly identified as community events 0 All events 39 Correlation with wind events 92.3% Correlation without wind events 92.3% 22

RMT 23 Aircraft operations correctly identified as aircraft events 3 1 1 1 Multiple aircraft operations correctly identified as aircraft events Community sources correctly identified as community events 4 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft Aircraft operations incorrectly identified as community events Community sources incorrectly identified as aircraft events 29 Wind noise incorrectly identified as aircraft event Wind noise incorrectly identified as community event 23

RMT #27 Anthony Middle School, 5757 Irving Avenue South, Minneapolis Aircraft operations correctly identified as aircraft events 14 Multiple aircraft operations correctly identified as aircraft events 1 Community sources correctly identified as community events 0 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 0 Aircraft operations incorrectly identified as community events 0 Community sources incorrectly identified as aircraft events 1 Wind noise incorrectly identified as aircraft events 0 Wind noise incorrectly identified as community events 0 All events 16 Correlation with wind events 93.8% Correlation without wind events 93.8% 24

RMT 27 Aircraft operations correctly identified as aircraft events 1 1 Multiple aircraft operations correctly identified as aircraft events Community sources correctly identified as community events Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft Aircraft operations incorrectly identified as community events 14 Community sources incorrectly identified as aircraft events Wind noise incorrectly identified as aircraft event 25

RMT #28 6645 15 th Avenue South, Richfield Aircraft operations correctly identified as aircraft events 12 Multiple aircraft operations correctly identified as aircraft events 2 Community sources correctly identified as community events 9 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 0 Aircraft operations incorrectly identified as community events 0 Community sources incorrectly identified as aircraft events 7 Wind noise incorrectly identified as aircraft events 0 Wind noise incorrectly identified as community events 0 All events 30 Correlation with wind events 76.7% Correlation without wind events 76.7% 26

RMT 28 Aircraft operations correctly identified as aircraft events 7 Multiple aircraft operations correctly identified as aircraft events Community sources correctly identified as community events 12 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft Aircraft operations incorrectly identified as community events Community sources incorrectly identified as aircraft events 9 2 Wind noise incorrectly identified as aircraft event Wind noise incorrectly identified as community event 27

RMT #30 8715 River Ridge Road, Bloomington Aircraft operations correctly identified as aircraft events 11 Multiple aircraft operations correctly identified as aircraft events 0 Community sources correctly identified as community events 3 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 0 Aircraft operations incorrectly identified as community events 1 Community sources incorrectly identified as aircraft events 1 Wind noise incorrectly identified as aircraft events 1 Wind noise incorrectly identified as community events 30 All events 47 Correlation with wind events 29.8% Correlation without wind events 87.5% 28

RMT 30 Aircraft operations correctly identified as aircraft events 11 Multiple aircraft operations correctly identified as aircraft events Community sources correctly identified as community events Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 30 1 3 0 1 1 Aircraft operations incorrectly identified as community events Community sources incorrectly identified as aircraft events Wind noise incorrectly identified as aircraft event Wind noise incorrectly identified as community event 29

RMT #33 North River Hills Park, Burnsville Aircraft operations correctly identified as aircraft events 0 Multiple aircraft operations correctly identified as aircraft events 0 Community sources correctly identified as community events 0 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 0 Aircraft operations incorrectly identified as community events 0 Community sources incorrectly identified as aircraft events 0 Wind noise incorrectly identified as aircraft events 0 Wind noise incorrectly identified as community events 0 All events 0 Correlation with wind events 100.0% Correlation without wind events 100.0% Note: There were no flight tracks or noise events observed or in the MACNOMS for this site during the time period of the field observation. 30

RMT #36 Briar Oaks & Scott Pond, Apple Valley Aircraft operations correctly identified as aircraft events 27 Multiple aircraft operations correctly identified as aircraft events 0 Community sources correctly identified as community events 0 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 0 Aircraft operations incorrectly identified as community events 0 Community sources incorrectly identified as aircraft events 0 Wind noise incorrectly identified as aircraft events 0 Wind noise incorrectly identified as community events 0 All events 27 Correlation with wind events 100.0% Correlation without wind events 100.0% 31

RMT 36 Aircraft operations correctly identified as aircraft events Multiple aircraft operations correctly identified as aircraft events Community sources correctly identified as community events Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft Aircraft operations incorrectly identified as community events Community sources incorrectly identified as aircraft events 27 Wind noise incorrectly identified as aircraft event Wind noise incorrectly identified as community event 32

Summary All RMT s: 5, 16, 23, 27, 30, 33, 36 Aircraft operations correctly identified as aircraft events 181 Multiple aircraft operations correctly identified as aircraft events 11 Community sources correctly identified as community events 18 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft 4 Aircraft operations incorrectly identified as community events 3 Community sources incorrectly identified as aircraft events 11 Wind noise incorrectly identified as aircraft events 1 Wind noise incorrectly identified as community events 30 All events 259 Correlation with wind events 81.1% Correlation without wind events 92.1% All RMTs Aircraft operations correctly identified as aircraft events 4 1 3 11 30 Multiple aircraft operations correctly identified as aircraft events Community sources correctly identified as community events 18 11 Multiple aircraft operations correctly identified as aircraft events but tagged to the other aircraft Aircraft operations incorrectly identified as community events 181 Community sources incorrectly identified as aircraft events Wind noise incorrectly identified as aircraft event Wind noise incorrectly identified as community event 33

Discussion Sound propagation from aircraft is the result of vibrations in air that are caused primarily by the aircraft s jet engines. However, there are also many instances when sound is propagated by a community source which is audible and detected by the RMT sound level meters; an even more complex situation arises when elevated wind speeds cause air pressure changes that are detected by the RMT microphone as an event of over 65 db for eight seconds. Wind events are barely audible on the audio playbacks and sound like a hiss. The sound level meter does not distinguish aircraft noise events, community noise events, or wind events from one another. The dissimilarity of noise patterns from wind and aircraft is shown in the charts below: Figure 2 Wind Event Sound Pattern at RMT 30 Figure 3 A320 Arrival Event Sound Pattern at RMT 5 These charts illustrate the importance of correlating the noise event to a flight track within the MACNOMS system as initially, based on noise levels derived exclusively from the RMT data, both patterns shown above met the event threshold. 34

Matching the noise event to a flight track is a function of the MACNOMS software that merges the Exelis data feed with the noise data sent by the RMT modems. In the current validation study, this merger was successful for 92% of the events observed in the field, following the manual flight track processing and noise match validation done by MAC staff. It is important to note that the automated functions of the MACNOMS are highly accurate. In short, the system is precise when there is an aircraft track that triggers an event at an RMT. The complex situations arise when there is an event at an RMT and no flight track recorded in the vicinity at the same time. These are generally assigned as a community event caused by a noise source, such as a lawn mower near the RMT, rather than an aircraft. Further complexity is introduced when the wind causes a noise event at the RMT and there was neither an aircraft nor a community noise source present. These wind events were prominent at RMT 30 during the field observation study and resulted in a higher percentage of community noise events matching. Wind and community noise events do not affect the operations counts or aircraft noise data that are contained in numerous MAC reports, including the monthly NOC Technical Advisor s Monthly Report. The correlation of events with and without the wind is shown on the chart below: 100.0% Figure 4 Correlation of Events 80.0% 60.0% 40.0% 20.0% 5 16 23 27 28 30 33 36 ALL RMT Correlation with wind events Correlation without wind events There were many instances of aircraft operations observed that did not trigger an event because the noise level at the specific RMT was less than 65dB for eight seconds. Again, the purpose of the event threshold is to minimize the events recorded that are caused by extraneous sources. 35

100 80 60 40 20 0 Figure 5 Observation & Event Counts 96 89 93 85 67 57 47 3633 39 33 37 30 27 16 5 16 23 27 28 30 33 36 RMT Observations Events When two aircraft tracks match one noise event recorded at an RMT, the MACNOMS software is programmed to assign the event at the RMT to one or the other flight. In Figure 6 below, an example is provided illustrating an Embraer 170 (E170) arriving on Runway 12L and an McDonnell Douglas 80 (MD 80) departing on Runway 17 within five seconds of one another. Figure 6 When the MACNOMS matches two flights that trigger an event at an RMT in nearly aligned timeframes, the software selects the louder of the two aircraft based on its Federal Aviation Regulation (FAR) Part 36 sound level certification. In this case the FAR Part 36 Take off Sound Level for an E170 is 83.7 and the MD 80 sound level is 91.5. The MACNOMS correctly selected the MD 80 as the source of the event at RMT 28. There were four instances out of 259 events (1.5%) during the validation study when the MACNOMS chose the higher FAR Part 36 take off sound level aircraft during multiple aircraft events. 36

Findings During the course of the MACNOMS Validation Study, MAC staff made some minor discoveries of processing issues that affected the data. These are described below: Daylight Savings Time (DST) Departure operations were recorded with a time stamp one hour earlier than the actual departure due to the change in DST in March 2014. A software programming correction was applied to the time stamp for departure operations. One Data Point Flight Tracks It was found that on rare occasions the Exelis Next Gen data feed would produce one data point for a flight track that did not occur. A proper flight track has hundreds of data points. This one data point flight track was reported to Exelis and the data feed for MSP was filtered to ensure one data point flight tracks are not included. Study constraints and limitations It is important to understand the limitations of this study. While conducting independent noise monitoring at sample RMT sites can provide valuable information as to what is occurring at the site and the overall accuracy of the MACNOMS, practical limitations do exist. At many of the RMT sites, multiple events may be occurring at any given time and therefore the scope of the data is limited to the individual abilities of the person performing the monitoring. In addition, practical limitations such as line of sight, audible range, and directionality of aircraft and community noise events may exist. Conclusions MACNOMS, owned and operated by the MAC is one of the largest arrays of noise monitors for a single airport in the United States. The extent of the noise monitoring coverage around MSP is expansive. Ever since the system was installed in 1992, extensive programming effort, hardware and software upgrades, and fine tuning have been done to ensure the highest degree of accuracy for noise to track correlation, noise measurement, and operations counts. MACNOMS is complex, robust, and stable; it provides reliable data output that is critical for the MAC Noise Programs Office and the public. This validation study involved 22 ½ hours of field noise measurement and observation at eight RMT sites and 8 ½ hours of runway observation from the MSP Orange Parking Ramp at Terminal 2 Humphrey. Although the sample selection was smaller than previous MACNOMS validation studies, the overall results were similar when compared to past reports, as shown in Table 8. 37

Table 8 Percentage of Noise Events Correlating with MACNOMS Flight Track Data 2014 2005 2004 2001 92.10% 94.30% 89.10% 90.90% Percentage of Observed Operations Correlating with MACNOMS Flight Track Data 97.10% 95.90% 96.80% 97.80% The report also determined that the sound levels measured by the sound level meters closely match those measured by the portable sound levels meters for identical aircraft overflight. There were a few minor software programming issues discovered including a daylight savings time correction for departures, a new filter to eliminate one data point flight tracks and a filter to eliminate squawk 1200 transponder beacon codes for operations at MSP. These corrections have been implemented with good results and no data was lost in the process. The study found that high wind speeds can trigger the recording of a noise event; however, there was only one instance of the MACNOMS assigning the wind event to a flight operation. There were a larger number of wind events that were assigned by the MACNOMS as community events, due to the lack of a flight track in proximity to the RMT when the wind event occurred. The wind events that were assigned as community events have no effect on the noise data reported by the MAC for aircraft operations at MSP. Overall, the 2014 MACNOMS validation study confirmed that the system is working within historical norms and its outputs have a high degree of accuracy and precision. 38

ITEM 7 MEMORANDUM TO: MSP Noise Oversight Committee (NOC) FROM: John Nelson, Manager Noise, Environment and Planning SUBJECT: Public Comment Period DATE: June 17, 2014 The Noise Program Office of the Metropolitan Airports Commission received a notice from NOC members Dianne Miller, City of Eagan, and John Bergman, City of Apple Valley (At-Large Community representative) that the following speaker will appear at the July 16, 2014 NOC meeting to discuss her concerns about the recent increase in operations off of Runway 17: Susan Friedline 4852 Wellington Court Eagan, MN A map showing the location of the property address (blue house outline) is shown below:

A table showing the arrival (Runway 35) and departure (Runway 17) counts from January 2014 through mid-june 2014 is shown below: MSP Runway 17 Departures and Runway 35 Arrivals by Month January 1 -June 16, 2014 January- 2014 February- 2014 March- 2014 April- 2014 May- 2014 June 1-16 2014 Runway 17 Departures 2,027 (12.2%) 2,225 (14.9%) 4,944 (27.1%) 3,528 (20.7%) 4,766 (27.6%) 2,757 (33.1%) Runway 35 Arrivals 3,768 (22.9%) 3,477 (23.4%) 3,146 (17.4%) 2,557 (15.1%) 2,460 (14.3%) 803 (9.7%) 6,000 5,000 4,000 3,000 2,000 2,027 3,768 3,477 2,225 4,944 3,146 3,528 4,766 2,557 2,460 2,757 Runway 17 Departures 1,000 0 803 Runway 35 Arrivals A staff review of flights on June 9, 2014 showed a typical south flow configuration with departures on Runways 17, 12R and 12L. When Runway 17 was being utilized for departures on that day, there were fewer departures to the south and west from Runway 12R. Those aircraft that were departing on Runway 12R were within the Eagan-Mendota Heights corridor, which generally places them on a 120-degree heading north of the south corridor boundary. Aircraft departing on Runway 12L maintain a heading south of the north corridor boundary before initiating turns to the north, northeast and west. Departure flight tracks from 8 a.m. to 4 p.m. on June 9, 2014 and the same time on June 9, 2013 are shown in the example FlightTracker maps below:

June 9, 2014 8 a.m. to 4 p.m. June 9, 2013 8 a.m. to 4 p.m.