Design of a Decision Support System to Reduce Radiative Forcing via Optimal Contrail Generation

Transcription

1 Abramson, Almofeez, Carroll, Margopoulos Certified Contrail-Optimal Route Design of a Decision Support System to Reduce Radiative Forcing via Optimal Contrail Generation 1 Images: [1],[2]

2 Overview Context System Development Simulation Results 2 Business Case

3 Controptimal System 1. Airline Dispatcher tool for flight plan generation 2. System uses weather data to find routes for optimal contrail generation Purpose: System seeks to proactively combat aviation s contributions to climate impacts 3

4 Context 4

5 Global Warming 1. Rising Sea Level (⅛ inch per year, 6.6 ft by 2100) [Climate Institute] Rising Global Temperature Extreme Storm Events Global warming effects are measured in terms of Radiative Forcing 5 1.,

6 Radiative Forcing Radiative Forcing: The heating of the Earth due to Sun s radiative heat being captured in Earth s atmosphere. Shortwave RF: Entering Earth Clouds help prevent RF from entering Earth. Net cooling effect (negative) Longwave RF: Leaving Earth Clouds prevent RF from leaving Earth Net warming effect (positive) 6 Clouds often occur naturally, but can also occur anthropogenically -- Contrails

7 Contrails and Aviation Contrails: Clouds that form in the wake of aircraft and can produce cloud formations under certain atmospheric conditions: Temperature: -40 C (or colder) Relative Humidity-i : 50% (or higher) Carbon Dioxide: Byproduct of flight CO 2 and H 2 O account for majority of aircraft emissions Main focus for emission reduction is on CO 2 7 [Euro Aviation Environmental Report]

8 Aviation Induced Radiative Forcing IPCC believes that contrails are the largest potential contributor to aviation based RF Potentially 5x more harmful than CO 2 Very little emphasis from airlines on contrail formation 8 [International Panel on Climate Change (IPCC, 2005)]

9 Contrail Formation Contrails occur in Ice Supersaturated Regions (ISSRs) Temperature: -40 C (or colder) Relative Humidity-i : 50% (or higher) From weather data analysis, it was found that ISSRs have pattern in altitude occurrence: FL have ISSRs peaking at 67% coverage Generally more likely to encounter contrails at higher altitudes 9

10 Problem RF due to contrails (1992): 0.05 W/m 2. RF due to contrails (2050): 0.19 W/m % Increase in RF. Air Traffic Growing 2.1% per year Radiative Forcing from air travel continues to increase as the number of flights increase, this leads to global warming. 10

11 Stakeholder Tensions Airlines FAA Citizens Congress 11

12 Need Statement No current system in place to mitigate contrail generation Need a system that will provide the following functions: 1. Reduce net RF 2. Factor fuel burn and time spent flying into decision analysis 3. Integratable into current National Airspace System (NAS) 12

13 System Development 13

14 Concept of Operations Controptimal is a system that encompasses a developed simulation in order to optimize when contrails are formed based on ISSR presence and time of day to reduce net radiative forcing. Morning: Contrail Seeking Evening/Night: Contrail Averse 14 END GOAL: Reduce Radiative Forcing via Contrails/Lack Thereof

15 Controptimal Functional Architecture Controptimal will serve as a DSS. Though airline dispatch and airline management work together, they have differing functions in the Controptimal system view. External User 15 Main System

16 Sequence Diagram Use case demonstrates typical use -- Airline Dispatch interacting with Controptimal Flight routes will be saved by Controptimal so that the system will be able to generate a history of how eco-conscious the airline is that will be using the system. 16

17 Requirements Mission Requirements Functional Requirements Non-Functional Requirements Design Requirements = Functional = Design = Mission = Non-Functional 17 Requirements Documented in CORE

18 IDEF0: 18 Functional Architecture Cont.

19 Simulation 19

20 Design of Simulation D.4.1 Derived Process: Test performance of 9 routes flying different altitudes to test if significant value in lower RF at different altitude D.4.2 The system shall demonstrate the capability of testing multiple flight plans over at time period of at least one month. Derived Process: Develop a network optimization using real-time weather data Derived Purpose: Opportunity to lower RF values more via optimized route planning. The system shall demonstrate the capability of flight planning for contrail generation optimization in real time Derived Purpose: Apply this information for airline dispatch 20

21 Methodology Location: Washington - Orlando Great Circle Distance (GCD) Altitudes: 29,000 ft - 45,000 ft Vertical Increments: 2,000 ft Dates: May 1 - August 31,

22 Simulation Design: Simulation Overview 22

23 Trajectory Track Trajectory Model Fuel Flow -BADA Aircraft Performance Tables for B737 -Fuel Burn for climb, cruise, descent. CO2 Emissions CO2 Emissions = f * c c = 3.175(kg CO2/kg fuel) RF - CO2 Model -The CO2 of a given flight is determined by relating the mass of CO2 released to a known ratio of CO2 release and radiative forcing caused: [Lee] A multiplier of 2.8 was found to be necessary to account for CO2 s emission at altitude. [5] 23

24 Weather Track 24 Weather Model Monte Carlo simulation May - August, 2015 Washington (IAD) - Orlando (MCO) Inputs: Solar Direct Radiation (SDR) Outgoing Longwave Radiation (OLR) Temperature (T) RF Contrail Model Solar Zenith Angle (SZA, µ) [Schumann]

25 RF Contrail Model Contrail RF based of Time of Year and Temperature Contrail RF Slope < 0 As ambient air temperature rises, contrail RF decreases Higher altitudes have more significant contrail RF 25

26 Data Flow 26

27 Design of Experiment Iterations for every hour, at every cruising Altitude (29K-45K) 2000 ft vertical separation Varying time BASELINE Alternative 1 Alternative 2... FL 350 FL 290 FL

28 Results 28

29 Simulation Flight Metrics Baseline Route Encounters ISSR Higher Net RF Alternative Route Encounters 1 ISSRs Lower Net RF $51.12/ Seat $51.93/ Seat 29

30 Simulation Results Bad The baseline flight, shown in blue, has a significantly high RF values that vary considerably with time. Alternatively, the optimal flight, shown in orange, is consistently hovering around 0 W/m 2 Good This demonstrates the opportunity to lower radiative forcing by flying at different altitudes. 30

31 Objectives Hierarchy Measures Include: time (min), Note: additional time above average represents increased operating costs Exponentially Decreasing SDVF Measures Include: Excess Fuel Burn, Linear Decreasing SDVF Measures Include: from Contrails, RF from CO2 (# turns) Linear Decreasing SDVF 31 Indicates lower is better

32 Simulation Results Flight plan statistics converted into utility via Single Dimensional Value Function (SDVF) values Tradeoff weights elicited stakeholder input Baseline Weight breakdown Net RF = 0.45 Fuel Burn = Duration = 0.18

33 Net RF Sensitivity Analysis Net RF Fuel Burn 33

34 Analysis Cont. Change in flight level has a major impact on aviation radiative forcing 85% reduction in net RF According to the trade-off analysis, the additional fuel burn is worth reduction in global warming impact 34 These results justify the creation of a contrail optimization software to be used by airline dispatchers

35 Methodology Location: Washington - Orlando Great Circle Distance (GCD) Altitudes: OPTIMIZED NETWORK Decision Variable: Altitude Dates: August 1,

36 Data Flow Matlab models are used to find fuel burn, net RF, and duration between all nodes 15 km intervals between nodes horizontally 1000 ft intervals between nodes vertically Python network package: NetworkX 36

37 Business Case 37

38 Business Case for Controptimal DSS Domestic airlines Customer Motivation Demand for Green Systems Public perception/reputation of airline in regards to environmental conservation efforts Lack of public knowledge on conservation efforts Enterprise Domestic air transportation system Gap Contrail optimization in commercial aviation market 38 Public awareness of environmental measures

39 Carbon Offset Program 39 [11]

40 Airline Business Case Environmental marketing study results About 25% out of 543 passengers agree that people should pay more for the negative environmental impact caused by aviation (Mayer, 2013) More than 95% of the environmental concern passengers (n=99) are willing to pay more for the negative environmental impact caused by aviation (Mayer, 2013) Airline investment in the environment improves public perception and provides an opportunity to increase profit 40

41 Business Model Subscription Service -- airlines subscribe for individual password access to Controptimal Airlines can earn a rating (gold, silver, bronze) based on the percentage of contrail optimal flight plans that are flown on a specific route Customers can see ratings when booking flights 41

42 Costs and Break Even Point Annual Fixed Costs Rent 100,000 Marketing 10,000 Equipment/software 50,000 Employees (10) 80,000 * 10 total $960,000 Variable Costs Support/certification 15,000 total $15,000 Break even point = 25 new yearly password subscriptions at $50,000 per password Break Even Time: Year 4 42

43 Conclusion Contrail formation is currently unmitigated by the flight planning procedures Controptimal uses an original simulation design to reduce aviation RF while minimizing the additional fuel burn and time Contrail mitigation strategy has business promise for airlines looking to market to environmentally conscious passengers 43

44 Thank you! Finding the path to a cleaner future 44 Abramson, Almofeez, Carroll, Margopoulos

45 References [1] N/A. FAA Aerospace Forecast, Fiscal Years faa.gov. March 24, [Online]. Available: [2] Penner Joyce E. IPCC Special Report, Aviation and the Global Atmosphere, 1999, Panel on Climate Change [3] Cosmic Convergence. Chemtrail Syndrome: A Global Pandemic of Epic Proportions cosmicconvergence.org. May 3, [Online]. Available: [4] U. Schumann. A Parametric Radiative Forcing Model for Contrail Cirrus [5] S. Ackert, Aircraft Payload-Range Analysis for Financiers, [Online]. Available: v1.pdf Pictures: [1] [2] [3] [6] N/A. Boeing Drag Project, N/A. [Online]. Available: [7] N/A. Aviation and Global Atmosphere, Section 4.8. N/A. [Online]. Available: [8] N/A. Fuel Mass Flow Rate, grc.nasa.org. May 5, [Online]. Available: 12/airplane/fuelfl.html [4] [5] [6] [7] [9] S. Paugam, Etude de la fromation d une trainee de condensation, [Online] Available: [10] D.Lee Anthropogenic and Natural Radiative Forcing N/A.. [Online]. Available: [8] [9] BADA, [10] 45 [11] N/A. CarbonChoice carbon offset program, N/A. [Online]. Availiable: US/content/company/globalcitizenship/environment/carbon-offset-program.aspx