DLR.de • Chart 1 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Operational measures for mitigating aircraft climate change Volker Grewe + contributions from many others DLR-Institute for Atmospheric Physics TU Delft, Chair for Climate Effects of Aviation ECATS Vice-Chair
DLR.de • Chart 2 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Comparison of emission of CO 2 equivalents (TgCO 2 /year) comprises CO 2 , CH 4 , NO 2 , SF 6 , HFCs, CFCs (without gases from the Montreal Protocol) Country % Change 1990 2000 2010 2015 / Type 1990-2015 Germany 1251 1043 942 902 -28% France 550 556 517 464 -16% Europe 5641 5151 4773 4307 -24% International 545 682 759 840 +54% 2014 Aviation Data: unfccc.int iea, 2016 • International Aviation • emits eq.CO 2 comparable to a large EU country • shows large increase in emissions
DLR.de • Chart 3 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Air traffic emissions at cruise IPCC (1999)
DLR.de • Chart 4 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Atmospheric effects of aviation CO 2 H 2 O NO x VOC, CO SO 2 Particles Emissions CO 2 H 2 O CH 4 O 3 Particles Contrails Changes in atmospheric composition Clouds Direct Indirect Direct Climate greenhouse greenhouse aerosol Clouds forcings gases gases effect Climate change
DLR.de • Chart 5 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Radiative Forcing in 2005 from historical aviation emission Carbon Dioxide, NO x emissions, and contrail cirrus are main contributors to aviation induced RF. Level of Scientific Understanding (LoSU) varies between individual effects Grewe et al. (2017) Data are based on Lee et al (2009) with update from various more recent publications
DLR.de • Chart 6 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Aviation´s impact on global mean 2m-temperature Main contributors : ~0.03 K von 0.7 K • CO 2 5% • Contrails • NO x (O 3 and CH 4 ) PMO=„Primary mode ozone“ Results from less CH 4 less HO 2 less O 3 production Air traffic contributes to climate change by roughly 5%.
DLR.de • Chart 7 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Mitigating the climate impact of aviation: Some recent studies - Technological Measures : DLR-Project CATS - Fuel efficiency Climatological approach - Emission reduction - Alternative fuels Aircraft redesign - Operational Measures : - Avoiding climate sensitive regions - Intermediate Stop Operations - Climate restricted airspaces Weather related approach - Economical Measures Implementation aspects - Market-Based Measures - Carbon off-setting EU-Projects REACT4C / ATM4E - Climate – Charged Areas DLR-Project WeCare / Eco2Fly
DLR.de • Chart 8 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change DLR-Project CATS: Climate Compatible Air Transport System Focus on a long-range aircraft =AirClim Koch et al., 2011 Dahlmann et al. 2016
DLR.de • Chart 9 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change CATS-optimisation approach • Variation of initial cruise altitude and speed • Optimal relation between costs and climate • Definition of new design point • Optimisation of the new aircraft for this new design point Koch, 2013
DLR.de • Chart 10 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change A330: Potential of a climate change reduction: CATS-results Variation in speed an cruise altitude 30% Reduction in climate change with 5% increase in costs 64% Reduction in climate change with 32% increase in costs (w/o adaption of aircraft) (Dahlmann et al, 2016)
DLR.de • Chart 11 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change CATS Final results Cumulative potential for all routes operated by redesigned A/C Max Mach 0.775 / Max Altitude 10500m Redesigned A/C considerably improves Koch (2012) climate impact mitigation potential and cost penalty
www.DLR.de • Chart 12 > Lecture > Author • Document > Date Can we make use of the large spatial variability in aviation non-CO 2 effects?
DLR.de • Chart 13 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Different weather situations: Evolution of aircraft NO x A B What happens if an aircraft emits NO x at location A compared to location B? Frömming et al
DLR.de • Chart 14 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Evolution of O 3 [ppt] following a NO x pulse A: 250hPa, 40°N, 60°W, 12 UTC B: 250hPa, 40°N, 30°W, 12 UTC Pressure [hPa] Frömming et al Change in NO x and Ozone mass EMAC-Symposium 14.-16. Februar 2012
DLR.de • Chart 15 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Weather data and Ozone Climate-Change-Functions Frömming et al. 2017
DLR.de • Chart 16 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Avoiding climate sensitive regions: The approach Traffic scenario: Respresentative weather situations Roughly 800 North Atlantic Flights Climatology based on Irvine et al. (2013) Climate-Change Functions Contrails, O 3 , CH 4 , H 2 O, CO 2 Traffic optimisation: With respet to costs and climate
DLR.de • Chart 17 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Climatology based on 8 representative weather pattern • Very flat Pareto-Front Large benefits at low costs • Market based measures (MBM) would enable climate optimised routing, if non-CO 2 effects were taken into account. Grewe et al. (2017)
DLR.de • Chart 18 > Lecture > Author • Document > Date Example: New York - London Clear difference between West- and eastbound traffic Minimal costs Larger overlap of routes Minimal climate impact
DLR.de • Chart 19 > Kolloquium OP> V. Grewe • > 18.0472016 Fleet basis • Only small differences visible • Smaller flight corridor • Difference between flights from and to Europe
DLR.de • Chart 20 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Air traffic management for environment: ATM 4E SESAR/H2020-Project ATM4E SWIM Current situation Matthes et al. (2017) ATM4E Overview > Sigrun Matthes, DLR > Intermediate Review, 18 May 2017 20
DLR.de • Chart 21 >DLR Climate Change Conference 2018> V. Grewe • Operational measures for mitigating aircraft climate change Air traffic management for environment: ATM 4E SESAR/H2020-Project ATM4E SWIM Contribution of ATM4E Matthes et al. (2017) ATM4E Overview > Sigrun Matthes, DLR > Intermediate Review, 18 May 2017 21
Algorithmic Climate Change Functions ATM 4E Latitude NO x -Ozone Climate Change Detailed calculation of Function Climate Change Functions Temperature Longitude Correlation with with weather data at time and location of the emission Geopotential Latitude NO x -Ozone Algorithmic Climate Change Function depending on Algorithmic Climate Temperature and Change Functions Geopotential Van Manen (2017) Longitude Van Manen and Grewe (2018) ATM4E WP5 Management > Intermediate Review, 18 May2017 22
Verification of the Algorithmic ATM 4E Climate Change Functions: Approach NO x Climate-sensitive Emissions Ozone regions (aCCFs) change Cost-optimal O 3 -RF of aircraft trajectory cost- optimal trajectory O 3 -RF of Arrival climate- optimal Climate-optimal trajectory aircraft trajectory Ozone Departure NO x change Emissions Radiatve Atmospheric Air traffic simulator Forcing Chemistry Yin et al. (2018) ATM4E WP5 Management > Intermediate Review, 18 May2017 23
Verification of the Algorithmic ATM 4E Climate Change Functions: Model Earth-System Model EMAC Great Circle ECHAM5/MESSy2.52 Atmospheric Chemistry Model Including: Air Traffic Simulator: AirTraf 1.0 • Aircraft/engine performance • Flight plan • Optimizer: Genetic algorithm • Fuel/Emissions Time optimal Chemistry • NMHC Chemistry (MECCA) Diagnostics • Tagging scheme Jet stream Yamashita et al. (2016) ATM4E WP5 Management > Intermediate Review, 18 May2017 24
Verification result ATM 4E RF: -2% Zonal mean ozone changes (mol/mol) The trajectories optimized using ozone aCCFs actually reduce the ozone climate impact. Proof of Concept Yin et al. (2018) ATM4E WP3: Verification 25
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