Climate impact of aviation NOx̳ emissions : radiative forcing, temperature, and temporal heterogeneity

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Climate Impact of Aviation NOx Emissions:

Radiative Forcing, Temperature, and Temporal

Heterogeneity

by

MASUA S U

OF TECHNOLOGY

Lawrence Man Kit Wong

OCT

0 2 201

B.S. Aerospace Engineering

Georgia Institute of Technology (2012)

Submitted to the Department of Aeronautics and Astronautics

in partial fulfillment of the requirements for the degree of

Master of Science in Aeronautics and Astronautics

at the

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

September 2014

@ Massachusetts Institute of Technology 2014. All rights reserved.

Signature redacted

Author...

Department of Aeronautics and Astronautics

Signature redacted

August 21, 2014

C ertified by ...

...

Steven R. H. Barrett

Associate Professor of Aeronautics and Astronautics

Thesis Supervisor

Signature

redacted-Accepted by ...

...

Paolo C. Lozano

Associate Professor of Aeronautics and Astronautics

Chair, Graduate Program Committee

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Climate Impact of Aviation NO, Emissions: Radiative

Forcing, Temperature, and Temporal Heterogeneity

by

Lawrence Man Kit Wong

Submitted to the Department of Aeronautics and Astronautics on August 21, 2014, in partial fulfillment of the

requirements for the degree of

Master of Science in Aeronautics and Astronautics

Abstract

Aviation NO, emissions are byproducts of combustion in the presence of molecular nitrogen. In the upper troposphere, NO, emissions result in the formation of 03 but also reduce the lifetime of CH4, causing an indirect reduction in the formation of 03. Meta studies by Lee et al. and Prather et al. concluded that the short-lived 03 radiative forcing (RF) was greater than the combined long-lived CH4 and 03 RFs,

leading to a net positive RF (4.5 to 14.3 mW/m2 _{per Tg of NO, emissions).} How-ever, few simulations assess the surface air temperature (SAT) response, or conduct a large ensemble simulation with climate feedback in the cases where SAT is predicted. We aim to quantify the climate forcing and temperature response of aviation NO, emissions. Eight 400-member ensemble simulations are conducted with an earth sys-tem model of intermediate complexity. Inter-scenario comparisons between emissions starting in 1991, 2016 and 2036 with mid-range and high anthropogenic emissions are performed. We then determine the existence of long-term temporal heterogeneity of climate forcing and impact.

The global net RF of an aviation NO, emissions inventory is positive from 1991 to 2100 while leading to a global average SAT responses of -0.068 K in 2100. Despite the positive zonal RF in the Northern Hemisphere of up to 413.9 mW/m2 _{at 45*N,} all latitudes experience cooling after 2075. In another scenario, constant aviation NO, emissions at 4.1 Tg/year cause a global net RF of near zero while leading to a SAT response of -0.020 K in 2100. The unexpected temperature behavior in both scenarios is attributed to the forcing from CH4 destruction being 64% more effective

in generating a SAT response than the 03 forcing. Despite the positive net RF, the probability of aviation NO. emissions being cooling is 67% because of the relative difference in 03 and CH4 efficacies.

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Comparing simulation results from six different scenarios, varying degrees of tem-poral heterogeneity exist in net RF, O RF and CH4 RF. However, there is insufficient

statistical significance to indicate temporal heterogeneity in SAT response based on current data.

Thesis Supervisor: Steven R. H. Barrett

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Acknowledgments

To say the past year, eight months and 17 days have been an interesting journey is an understatement. As I near the completion of this thesis, I had to remind myself this endeavor is no different from the times when we were utterly exhausted, drenched, out in the fields. Positive self-talk, take a deep breath and, most of all, never let go. I am fortunate that this expedition is not one that I had to make alone. I am forever indebted to my family for their unwavering support. The freedom and en-couragement to pursue my passion are endowments that I do not take for granted. I hope, in however small way, this study has contributed to the furthering of knowledge and that it will add to the effort in preservation of the environment we so love.

I also cannot thank my advisor, Prof. Steven Barrett, enough for the inspiration, knowledge and patience. Venturing into a new field is a daunting task. Thankfully, I was not flying in the dark given the guidance from a leader with such wisdom and acumen.

I am also grateful for the opportunity to work with my colleagues Irene Dedoussi, Akshay Ashok, Philip Wolfe and others. I thank you for the fellowship and the laughters. It is amazing to know that we are in this together. Despite my primary field of performing climate assessments, GEOS-Chem runs have never been a more enjoyable experience.

Last, my earnest appreciation goes to Jennifer Plotkin. Thank you for keeping me strong through the darkest hour. My words fail me in expressing how blessed I am to run into you in my first class at MIT.

I dedicate this work to a very special friend, who paid the ultimate sacrifice in protection of this community. A man who taught me what it means to live in the service of others, who exhibited the true spirits of "So that others may live".

Greater love hath no man than this, that a man lay down his life for his friends.

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List of Figures

2-1 The transient (scenario 1) aviation NO, emissions profile. The proffile assumes 88% of NO, is emitted as NO. . . . . 19 2-2 The spatial configuration of aviation NO, emissions. The bulk of the

emissions are centered just below the tropopause of the northern hemi-sphere. . . . . 20

2-3 Comparison of anthropogenic emissions of species relevant to NO.-03

-CH4 reactions between the EPPA-generated emissions scenario (high

greenhouse gases emissions) and RCP 4.5 Similar (mid-range RF sta-bilization scenario). . . . . 21 3-1 RF response to transient aviation NO, emissions from 1991 to 2100.

Net RF remains positive over the entire time horizon. The shaded region illustrates 15-85% confidence interval. . . . . 24 3-2 03 RF response to transient aviation NO., emissions in comparison

with emissions profile. . . . . 25 3-3 RF response to constant aviation NO, emissions (on an NO2 mass

ba-sis) at 2016 level (4.1 Tg/year). Net RF decreases to approximately zero beginning in 2014. The shaded region illustrates 15-85% confi-dence interval. . . . . 25 3-4 Zonal RF response to transient aviation NO, emissions. At 45*N in

2100, net RF reaches 206.7 mW/m2 _(a);_03R_{F reaches 719.2 mW/M}2 (b); CH4 RF reaches -242.5 mW/m2 (c). . . . . 27

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3-5 Zonal RF response to constant aviation NO, emissions. At 45*N in 2100, net RF reaches 129 mW/m2 _(a);₀₃_{RF reaches 206.7 mW/M}2 (b); CH4 RF reaches -60.9 mW/M2 (c) . . . . . . . . . . 28

4-1 SAT response to transient aviation NO, emissions from 1991 to 2100. SAT remains around zero until 2020 and decreases to -0.068 (-0.141, 0.000) K by 2100. . . . . 30 4-2 SAT response to constant aviation NO, emissions from 1991 to 2100.

SAT decreases from 0.001 (-0.040, 0.040) K in 1991 to -0.020 (-0.091, 0.052) K by 2100. . . . . 31 4-3 Zonal SAT response to transient aviation NO, emissions. The majority

of the latitudes experience mild warming in 1992. . . . . 33 4-4 Hemispherical or regional mean temperature response to transient

avi-ation NO, emissions. The Southern Hemisphere (SH) starts experi-encing cooling in 1997 while the Northern Hemisphere (NH) warming persists until 2039. The flight corridor (20*N to 60*N) experiences cooling beginning only in 2075. . . . . 34 4-5 Zonal SAT response to constant aviation NO, emissions. All latitudes

north of 80 *S experience warming in 1992. . . . . 34 4-6 Hemispherical or regional mean temperature response to constant

avi-ation NO, emissions. The Southern Hemisphere (SH) starts experi-encing cooling in 1995 while the Northern Hemisphere (NH) warming persists until 2004. The flight corridor (20*N to 60*N) experiences cooling beginning only in 2030. . . . . 35

5-1 The global net RF response to aviation NO, emissions beginning in 1991 (Baseline), 2016 or 2036 with high background emissions (EPPA) or mid-range background emissions (RCP 4.5 Similar). The shaded region illustrates one standard deviation of the Baseline simulation with mid-range background emissions. . . . . 39

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5-2 The global 03 RF response to aviation NO., emissions beginning in 1991 (Baseline), 2016 or 2036 with high background emissions (EPPA) or mid-range background emissions (RCP 4.5 Similar). The shaded region illustrates one standard deviation of the Baseline simulation

with mid-range background emissions. ... 40

5-3 The global CH4 RF response to aviation NO. emissions beginning in

1991 (Baseline), 2016 or 2036 with high background emissions (EPPA) or mid-range background emissions (RCP 4.5 Similar). The shaded region illustrates one standard deviation of the Baseline simulation

with mid-range background emissions. ... 41

5-4 The global SAT response to aviation NO, emissions beginning in 1991 (Baseline), 2016 or 2036 with high background emissions (EPPA) or mid-range background emissions (RCP 4.5 Similar). The shaded region illustrates one standard deviation of the Baseline simulation with

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List of Tables

2.1 Eight aviation NO, emissions scenarios are used, including an emis-sions projection to 2100 and 7 other constant emisemis-sions cases to assess steady-state climate forcing and temperature response. . . . . 18

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Chapter 1 Introduction

Nitrogen monoxide (NO) and nitrogen dioxide (NO2) (collectively, nitrogen oxides,

NO,) are formed when combustion occurs in the presence of molecular nitrogen, such as the atmosphere. Its production is favored in an environment of high temperature, high pressure and long residence time. This characteristic creates a tradeoff with other emissions species, such as carbon dioxide, and flame stability. Haselbach and Parker found that between optimizing an engine design for NO, emissions and fuel consumption (and therefore carbon dioxide emissions) led to a NO, increase of 30% [1].

When emitted in the upper troposphere, NO. emissions result in the formation of ozone (03) (a greenhouse gas, therefore generating a positive radiative imbalance) and increase hydroxyl radical (OH) concentrations, which results in the removal of methane (CH4) (removal of a greenhouse gas, hence creating a negative radiative

imbalance) [2]. A secondary 03 reduction (negative radiative imbalance) is associated with the the removal of CH4 [3]. Comparing to the one-year timescale of

inter-hemispheric mixing, the effect of the 03 formation on radiative imbalance is short-lived (lasting about a month), creating a hemispheric impact, while that of CH4 reduction is long-lived (decadal) and global [4].

Aviation is estimated to have emitted 2.7 Tg of NO, (on an NO2 mass basis) in 2005 [5], which almost doubled the quantity in 1992 [6]. Despite the anticipated improvement in NO, reduction technologies, the annual increase in air travel demand

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by 4.2 to 4.9% [7 is projected to create a growth of NO, emissions to 13 Tg/year in 2050

[8].

Aviation emissions currently account for about 5% of anthropogenic emissions but are expected to become proportionally more in the future, especially in countries where other anthropogenic emissions are declining.

Radiative forcing (RF) quantifies the change in energy fluxes at some level in the atmosphere caused by natural and anthropogenic substances, relative to preindustrial conditions [9]. Emissions of greenhouse gases cause a positive RF. Greenhouse gases absorb the outgoing infrared radiation and re-emit it in all directions, including a component that heats the lower layers of the atmosphere and the surface [9].

From a positive radiative imbalance comes a positive temperature response, or global warming. The same magnitude of forcing from different chemical species or different geospatial configuration can trigger different climate feedbacks, therefore leading to different temperature responses [101. Moreover, extratropical surface tem-perature response is more sensitive to forcing location than tropical or global mean surface temperature response [11}. Global and zonal surface temperature changes directly impact crop growth cycle, biodiversity, etc. and are more tangible metrics than RF [4, 12, 131.

Variation in solar radiation intensity changes the rate of photolysis, which govern the intermediate steps of 03 formation. Gilmore et al. found that aviation NO, emitted in October causes 40% more 03 than April [14].

The objectives of this study is to quantify the time progression of both global and zonal mean temperature responses from aviation NO. emissions and to assess whether the climate forcing and temperature response change due to emissions time and atmospheric background conditions (long-term temporal heterogeneity).

Using an earth system model of intermediate complexity, the climate forcing and response are quantified. Chapter 2 details the methods and assumptions of the sim-ulations. Chapter 3 shows the climate forcing. Chapter 4 presents the temperature response. Chapter 5 discusses the temporal heterogeneity of climate responses from aviation NQ, emissions. Chapter 6 provides a conclusion to review the climate impact of aviation NO, emissions from the simulations.

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Chapter 2 Methods

This chapter details the methods of estimating the climate forcing and temperature response from aviation NO. emissions. We perform numerical simulations with an earth system model of intermediate complexity, Integrated Global Systems Model (IGSM). Eight aviation emissions (NO, only, other aviation emissions are not in-cluded) scenarios are used. Each scenario is analyzed through a 400-member ensemble simulation to determine the mean climate forcing and temperature response. Inter-scenario comparisons are then used to determine the existence of long-term temporal heterogeneity. The details to each of the components are given below.

2.1 Emissions Scenarios

Eight different emissions scenarios are used, as shown in Table 2.1. Emissions scenario 1 is used to quantify the climate impact of a high-growth aviation NO. emissions projection from 1991 to 2100. Emissions scenarios 2 and 3 are used to capture the steady-state climate forcing and temperature response of aviation NO, emissions for computation of efficacies (see Ch.4). In addition, emissions scenarios 2, 4 - 8 are used to assess if emissions beginning in different years and atmospheric background concentrations result in a different climate forcing and temperature response.

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Table 2.1: Eight aviation NO, emissions scenarios are used, including an emissions projection to 2100 and 7 other constant emissions cases to assess steady-state climate forcing and temperature response.

Scenario Aviation NO, Emissions Anthrop. Emissions

1 ACCRI Baseline EPPA

2 Constant at 2016 rate; introduced in 1991 EPPA

3 Constant at 5x2016 rate; introduced in 1991 EPPA

6 Constant at 2016 rate; introduced in 1991 RCP 4.5 Similar 7 Constant at 2016 rate; introduced in 2016 RCP 4.5 Similar

8 Constant at 2016 rate; introduced in 2036 RCP 4.5 Similar

2.1.1 Aviation Emissions

The aviation emissions inventory used assumes 88% of NO, is emitted as NO. The transient aviation NO, emissions profile is adapted from the Baseline scenario of the Federal Aviation Administration (FAA) Aviation Climate Change Research Initiative (ACCRI) [8]. The inventory from 1991 to 2005 is based on historical emissions. The values from 2006 to 2050 represent a projection of global aviation emissions growth while assuming aircraft technology fixed at 2006 level with no engine NO, technology improvements other than those achieved through fleet evolution. The profile is linearly extrapolated to 2100 by assuming the same emissions growth rate from 2036 to 2050. Figure 2-1 shows the time evolution of the emissions profile.

The magnitudes of the constant aviation NO, emissions profiles are fixed at either the 2016 level (4.1 Tg/year) or that scaled five times (20.5 Tg/year). Scenarios 2 and 3 are used for the computation of efficacies (see Ch.4). To assess long-term temporal heterogeneity, emissions profiles 4, 5, 7, and 8 contain a delayed introduction of aviation NO, in 2016 or 2036.

Climate impacts of aviation NO, emissions differ based on the location of emis-sions. K6hler et al. showed that 03 production efficiency increases with altitude [15J. Gilmore et al. found that flights to and from Australia or New Zealand generate the highest 03 burden when normalized by fuel burn [141. In all simulations of this study,

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3_0r 25- 20- 15- S10-x 0 5-0 2000 2020 2040 2060 2080 2100 Year

Figure 2-1: The transient (scenario 1) aviation NO, emissions profile. The profile assumes 88% of NO, is emitted as NO.

the aviation NOx emissions profiles are gridded at 4' latitude by 2000 ft altitude, with bulk of the emissions being centered between 20'N and 60*N, 400 hPa and 250 hPa (Figure 2-2). The spatial configuration of emissions are assumed to be fixed over time.

2.1.2 Anthropogenic Emissions

Ambient concentrations of hydrocarbons, carbon monoxide, and other trace species influence the reaction rates [16]. In turn, the concentration of 03 influence that of OH and thereby CH4. Nonlinearity in ozone production efficiency with respect to

NOx concentration exists [17, 18]. Therefore, it is important to quantify the climate forcing and temperature response of aviation emissions in different projections of non-aviation emissions because of the potential for interactions between the non-aviation and non-aviation emissions.

The Intergovernmental Panel on Climate Change (IPCC) developed four storylines of future energy use until 2100 and derived 40 emissions scenarios [19]. In 2013, the IPCC adopted four Representative Concentration Pathways (RCP) for use in climate

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1.8 100 200 1.4 300 CU 400 CU CU 500 600 0.8 700 0.6 _a) 800 _0.4_M 900 0.2 0-1000 L 90S 45S 0 45 N 90 N Latitude

Figure 2-2: The spatial configuration of aviation NO, emissions. The bulk of the emissions are centered just below the tropopause of the northern hemisphere.

assessments. The RCPs provide higher spatial resolution (mostly at a 0.5 by 0.5 degree) in annual greenhouse gas concentrations and anthropogenic emissions up to 2100 [9].

In this study, the non-aviation emissions are either generated by the Emissions Prediction and Policy Analysis (EPPA) module of IGSM [20] or modeled with val-ues that mimic RCP 4.5, which we term RCP 4.5 Similar. Figure 2-3 compares the emissions levels of species relevant to NO,-03-CH4 reactions. When compared

with the RCP scenarios, the EPPA-derived CO2 emissions are aligned with RCP 8.5

through 2045 and then grow to a maximum of 75.7 Pg in 2070 before decreasing to the 2045 level in year 2100. The scenario portrays a high greenhouse gases emissions future. The alternative scenario is similar to RCP 4.5, which describes a future where greenhouse gases emissions are released in such a way to stabilize at a midrange RF value of 4.5 W/m2 _{by 2100. We observe that CH}

4 emissions are higher in the EPPA-generated scenario than the alternative scenario. The reaction with CH4 is a major sink of hydroxyl radicals (OH), which is the main oxidizing agent in the atmosphere and influences the removal of 03 and conversion within the NO, family [16]. The

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higher NO, emissions in the EPPA-generated scenario also lead to a different ozone production efficiency between the two groups of simulations [17].

80 60 40 20 2000 2050 2100 Year 0 0 CUD 02000 2050 2100 Year 4 3 2 2000 2050 2100 Year 0~ I 0 50 00 502000 2050 2100 Year 1 0.8 0.6 0.4 0.22000 2050 2100 Year -- EPPA - RCP 4.5 Similar

Figure 2-3: Comparison of anthropogenic emissions of species relevant to NO2-03

-CH4 reactions between the EPPA-generated emissions scenario (high greenhouse gases

emissions) and RCP 4.5 Similar (mid-range RF stabilization scenario).

2.2 Integrated Global System Model (IGSM)

IGSM [211 is an earth system model of intermediate complexity. The model incorpo-rates a coupled atmosphere-ocean-land model linked to other models that simulate climate-relevant processes. The anthropogenic and natural emissions drive the cou-pled atmospheric chemistry and climate models. The outputs then determine water and energy budgets, C02, CH4, and N20 fluxes, and soil composition, which are fed

back to the coupled chemistry and climate models.

The simulations are done using IGSM version 2.2, which includes an atmospheric dynamics and physics model discretized into 46 latitude bands and 11 altitude levels. The global atmospheric chemistry module includes 33 chemical species and account for

0~ N 0 0 300 200 0 Z 100 2

05;;P0

1 1

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41 gas-phase and twelve heterogeneous reactions. The ocean model is discretized into grids of 40 latitude by 5* longitude. Heat diffusion into deep ocean is characterized by diffusion coefficients that vary temporally, zonally and meridionally. The terrestrial water, energy, and ecosystem processes are simulated with models discretized into grids of 4* latitude by 4* longitude. Time-steps used in the various sub-models range from 10 minutes for atmospheric dynamics, to 1 month for the changes in crops and forest productivity.

IGSM was compared with six other 3D climate models on the effect of aviation emissions on atmospheric 03 and CH4 by Olsen et al. [6]. The model was found to

perform within the envelop of the 3D models in terms of concentration profile and RF predictions for 2006 and 2050 emissions inventories derived from the Aviation Environmental Design Tool (AEDT), which is the same as the emissions used here.

2.3 Ensemble Simulation

Ensemble simulation is needed to separate the relatively small signal of climate change attributable to aviation from natural climate variability [4]. A 400-member paired Monte Carlo ensemble simulation is applied for each emissions scenario using the perturbed-parameter ensemble (PPE) approach [9]. In each of the member simulation, model parameters (effective climate sensitivity, the rate at which heat is mixed into the deep oceans, and the strength of the aerosol forcing associated with a given aerosol loading) are varied based on values from statistical analyses [22]. This approach was used to produce probabilistic climate forecasts for various anthropogenic emissions scenarios and policy assessments [23, 24].

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Chapter 3 Radiative Forcing

This chapter presents the effect of aviation NO, emissions in terms of RF. Distinctions are made between instantaneous RF (RFi), stratospherically adjusted RF (RFa), and the recently introduced concept of effective RF (ERF) [9]. RFi represents the radiative imbalance at a specific altitude without allowing the system to adjust to the forcing whereas RFa and ERF allow rapid adjustments in either the stratosphere only or both stratosphere and troposphere respectively. Rapid adjustments, e.g. cloud properties, are distinct from climate feedbacks in that they are not caused by changes in surface temperature. These adjustments are especially relevant to the quantification of the climate impact of aerosols. In this study, the values reported are RFi estimated at the tropopause.

The net RF of aviation NO, emissions is positive, albeit highly uncertain [4, 25].

Lee et al. reported that the net RF of aviation NO, emitted in 2005 (0.88 Tg N) was found to be 12.6 (90% confidence range 3.8, 15.7) mW/m2_{, with 03 contributing 26.3}

(8.4, 82.3) mW/m2 _{and CH}

4 -12.5 (-76.2, -2.1) mW/M2 [26] . Holmes et al. conducted

a metaistudy to conclude that the net RF from 1 Tg of aviation NO, emissions was 4.5 mW/m2 _{with an equal magnitude of uncertainty [25]. The RF of short-lived 03} effects was found to be 27.3 9.7 mW/m2_{, long-lived CH}

4 effects -16.1 5.6 mW/M2,

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3.1 Global Mean RF Response

3.1.1 Transient Aviation NO, Emissions

In scenario 1, the net global average RF reaches a maximum of 32.2 mW/m2 (10-year rolling average, 15-85% confidence interval (21.4, 41.6) mW/m2_{) in 2060 and} remains positive for the entire time horizon (Figure 3-1). 03 RF grows approximately proportionally to NO, emissions (Figure 3-2) while the effect of CH4 loss accumulates

due to its decadal lifetime.

300 200 100 -E 0 0 200 --Net - 03 -CH 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Year

Figure 3-1: RF response to transient aviation NO, emissions from 1991 to 2100. Net RF remains positive over the entire time horizon. The shaded region illustrates 15-85% confidence interval.

3.1.2 Constant Aviation NO, Emissions

Applying scenario 2, the net RF decreases from 31.8 (1.60, 60.2) mW/m2 _{in 1991 to} approximately zero beginning in 2014 (0.314 (-10.3, 10.2) mW/M2_{) (Figure 3-3). The} net RF is dominated by the 03 RF in 1991. The 03 RF then grows to 64.3 (59.0,

71.0) mW/M2 _{in 2100. The CH}

4 RF begins at -1.10 (-1.40, 0.00) mW/M2 in 1991 and

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30 300

- NOX emission rate

..- NOX-03 _RF 25 -- 250 20- _-₂₀₀_M E 15 - -150 c 0 0 z z 10- -100 5- -50 0 2000 2020 2040 2060 2080 210 Year

Figure 3-2: 03 RF response to transient aviation NO. emissions in comparison with emissions profile. 1 0 0 - - .. - . - ... ... ... .... .... 60 -20 .... E LL O -20-z - 4 0 -... . .... .. . .... .. .. .... ... .-.. - 60 -. . .--...... -8 0 - .-. -.. .. .. ... .-.. .. ... -. . -. - ... ... . ... -- Net .- 03 - 4C 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Year

Figure 3-3: RF response to constant aviation NO, emissions (on an NO2 mass basis)

at 2016 level (4.1 Tg/year). Net RF decreases to approximately zero beginning in 2014. The shaded region illustrates 15-85% confidence interval.

For each teragram of NO, emissions, the 03 RF is 15.3 (13.8, 16.8) mW/m2 _and that of CH4 is -14.5 (-15.0, -14.0) mW/m2 (average between 2080 and 2100). These

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values are within the bounds reported by Lee et al. and Holmes et al.

3.2 Zonal Mean RF Response

3.2.1 Transient Aviation NO, Emissions

In scenario 1, the zonal net RF is characterized by a sign change approximately at the equator (Figure 3-4) due to the competition between two dominating RF components, 03 and CH4. Being a short-lived forcing, the 03 RF is highest along the path of

emissions (20*N to 60'N) and spreads poleward due to the northerly circulation of 03. At 45-N, the 03 RF starts at 46.6 mW/m2, increases to 206.2 mW/m2 in 2030 and reaches 719.2 mW/m2 _{in 2100. The CH}

4 RF values are more zonally homogenous. At the same latitude, the CH4 RF is -0.9 mW/m2 in 1991, decreases to -48.7 mW/m2 in 2030 and reaches -242.5 mW/m2 _{in 2100. With the magnitude of tropical CH}

4 RF growing at a faster rate than the 03 RF, the boundary where the net RF changes signs migrates towards the north over time. We observe that the maximum zonal 03 RF is about three times the magnitude of zonal CH4 RF. However, the CH4 RF

covers a much wider area for a given year.

3.2.2 Constant Aviation NO. Emissions

For scenario 2, the net RF is characterized approximately by latitudinal stratification in the Northern Hemisphere (Figure 3-5). Net RF peaks at 45*N (129 mW/m2_{) while} the net RF at 86*N oscillates between 48 and 69 mW/m2_{. A band of "RF neutral"} zone exists around 20*N beginning in 2020. Similar to scenario 1, the Southern Hemisphere sees a zonally homogeneous net RF that is increasingly negative over time. The highest 03 RF is close to the emissions zone. At 45*N, the 03 RF starts at 97.1 mW/m2_{, increases to 133.2 mW/m}2 _{in 2030 and reaches 206.7 mW/M}2 _in 2100. Nonlinearity of 03 production efficiency possibly exists (see Ch.5). At the same latitude, the CH4 RF starts at -2.0 mW/m 2, decreases to -43.1 mW/m2 in 2030 and reaches -60.9 mW/m 2 _{in 2100.}

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a. Net RF (mW/m2) 2000 2020 2040 2060 2080 b. 0, RF (mW/m2) 90 N 45 N 0 45S 90 S 90 N 45 N 0 45S 90S 90 N 45 N 0 45S 90S

;uuu ZU4U _zubu

Year

Figure 3-4: Zonal RF response to transient aviation NO, emissions. net RF reaches 206.7 mW/m2 (a); 03 RF reaches 719.2 mW/M2 _(b);

-242.5 mW/m2 _(c). At 45*N in 2100, CH4 RF reaches 0 0 (U -J .0 2000 2020 2040 2060 2080 C. CH4RF (mW/m2) 2100 700 600 500 400 300 200 100 0 -100 -200 2100 2100

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90 N 45 N 0 45S 90 S 90 N 45 N 0 45S 90S 90 N 45 N 0 45S 90S a. Net RF (mW/m2) 2000 2020 2040 2060 2080 b. 03 RF (mW/m2) 2100 2100

dUUU 2uzu 2U4U zubu 2odU

C. CH4RF (mW/m2) 2000 2020 2040 2060 2080 Year 2100 200 150 100 50 0 -50

Figure 3-5: Zonal RF response to constant aviation NO. emissions. At 45'N in 2100, net RF reaches 129 mW/M2 _{(a); 03 RF reaches 206.7 mW/m}2 _{(b); CH}

4 RF reaches -60.9 mW/m2 _(c).

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Chapter 4 Temperature

This chapter discusses the surface air temperature (SAT), defined as air temperature at 2 m above ground or sea, response of aviation NO, emissions. Global and zonal surface temperature changes directly impact crop growth cycle, biodiversity, etc. and are more tangible metrics than RF [4, 12, 13]. However, increased uncertainty is caused by its dependence on the model representation of climate feedbacks and natural variability. An ensemble of simulation is also needed to separate the small signal of aviation from noise and to quantify statistical uncertainty.

Previously, the temperature response of aviation NO, emissions was quantified with the application of simple climate models (SCMs) [27, 28, 29] and atmosphere-ocean general circulation models (AOGCMs). The use of SCM is highly sensitive to the results of the more detailed model that it is tuned to, which may not account for nonlinearitoie at future emissions levels. The computational demand of AOGCM pre-cludes the use of large ensemble simulations. Olivi6 et al. used a 3-member AOGCM simulations to predict the SAT response of non-CO2 effects from aviation (which

in-clude not only NO, but also aerosols, contrails and aviation-induced cirrus) in 2100 to be 0.144 0.012 K [30]. Huszar et al. used another 3-member ensemble simula-tion with an AOGCM with prescribed tropospheric CH4 scheme to find no significant

global mean SAT response from aviation NO, emissions by 2100. Nevertheless, zonal warming and cooling of up to 0.3 K is present [31].

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4.1 Global Mean SAT Response

4.1.1 Transient Aviation NO, Emissions

The SAT response from scenario 1 starts at 0.003 (-0.038, 0.042) K in 1991 and remains about zero until 2020. This lag reflects the large time constant (climate inertia) for the global SAT to respond, especially from small forcing, such as that from current day aviation NO, emissions relative to all anthropogenic emissions. The SAT then decreases approximately at a constant rate to -0.034 (-0.087, 0.012) K in 2080 and the gradient steepens to reach an SAT of -0.068 (-0.141, 0.000) K by 2100

(Figure 4-1). 0.1 -0 .0 5 -... -. ... . ... .. . .. .. ... ... .. . 0 -0.05 --0.1 0.15 --0.2- -..... -0.25- _{2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100} Year

Figure 4-1: SAT response to transient aviation NO, emissions from 1991 to 2100. SAT remains around zero until 2020 and decreases to -0.068 (-0.141, 0.000) K by 2100.

4.1.2 Constant Aviation NO, Emissions

For scenario 2, the SAT decreases from 0.001 (-0.040, 0.040) K in 1991 to -0.020 (-0.091, 0.052) K by 2100 at a rate that is approximately constant. (Figure 4-2). It is

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observed that in both the simulations of scenarios 1 and 2, there is a transient SAT increase between 2020 and 2040.

0 .0 6 - -. .... ..... .. 0.02 0 -0.02 0 -0.04 -0.068 ... 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Year

Figure 4-2: SAT response to constant aviation NO. emissions from 1991 to 2100. SAT decreases from 0.001 (-0.040, 0.040) K in 1991 to -0.020 (-0.091, 0.052) K by 2100.

4.1.3 Efficacies

The net RF of scenarios 1 is positive over the entire simulated time horizon while that of scenario 2 begins in the positive and decreases to near-zero in 2014. Yet, both simulations result in a negative SAT by 2100. The result disagrees with the expectation that a positive (net) RF leads to a positive SAT.

Nonetheless, this unexpected temperature behavior can be explained by the non-unity efficacies of 03 and CH4. Efficacy measures how effective a given forcing is

in generating a temperature response. Inhomogeneous forcings, including 03 and contrails, may have efficacies that deviate significantly from unity [4, 32].

As aviation NO, emissions lead to a positive 03 RF and a negative CH4 RF,

its SAT response combines the product of component RF and its climate sensitivity parameter, A. The climate sensitivity parameter is the constant of proportionality

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relating RF to SAT at steady-state [4, 32]. A system of equations relating SAT to the product of climate sensitivity parameter and RF can be set up as

SATs2 RFo,s2 RFCH4,S2 A0 3

SATs3 RF_{0 3},s3 RFCH4,S3 ACH4

where S2 and S3 indicate scenarios 2 and 3 respectively. Using results from scenarios 2 and 3, where the ratios between SAT response and the 03 and CH4 component

RFs are approximately constant between 2080 and 2100, we approximate the steady-state response and carry out a matrix inversion to calculate the climate sensitivity parameters. Efficacies are then calculated by taking the ratio of the climate sensitivity parameters with respect to that of CO2 [4, 32].

The efficacy of aviation NO-induced CH4 depletion was found to be 1.26, while

that of aviation NO-induced 03 formation was 0.77 [33]. For the efficacies reported, the ratio of 03 RF to CH4 RF (RF ratio) has to be 1.64 to achieve a zero SAT. Using the mean and standard deviation of RFs reported by Holmes et al. [25], the probability of the RF ratio smaller than 1.64 is 67%, which we conclude as the probability of aviation NO being cooling.

4.2 Zonal Mean SAT Response

4.2.1 Transient Aviation NO, Emissions

In scenario 1, the majority of the latitudes experience warming (averaging 0.003 K but up to 0.010 K at 70*N) in 1992 (Figure 4-3). Huszar et al. also reported the maximum temperature increase to occur at the Arctic in the near term [31]. The band of latitudes that experience warming shrinks and is restricted to the Northern Hemisphere after 2035.

With the homogenous and accumulative effect of CH4 destruction, the Southern Hemisphere starts experiencing cooling beginning in 1997 (Figure 4-4). Since the 03 effect is hemispheric, the Northern Hemisphere continues to be warmed up to 0.005

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90 N

I

0 45 N -0.05 -0.15 45S -0.2 90S 2000 2020 2040 2060 2080 2100 Year

Figure 4-3: Zonal SAT response to transient aviation NO, emissions. The majority of the latitudes experience mild warming in 1992.

K until 2039 whereas the flight corridor (20*N to 60*N) is warmed up to 0.009 K until 2075.

4.2.2 Constant Aviation NO, Emissions

For scenario 2, warming occurs at all latitudes north of 80*S in 1992, averaging to 0.004 K with a peak at 0.014 K at 70 *N. An episode of warming above 0.002 K affects 30_{N to 90*N until 2012 (Figure 4-5).}

As shown in Figure 4-6, the Southern Hemisphere is warmed to 0.002 K in 1991 but drops below zero at 1995. The hemisphere is cooled approximately at a fixed rate to -0.042 K in 2100. The Northern Hemisphere is warmed until 2004 and experiences cooling for all years after. Focusing on just the flight corridor, warming persists until 2030.

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0.02r 0 -0.06 -0.08--0.1 -0.12 -0.14 - Flight Corridor -NH -SH 2000 2020 2040 Year 2060 2080 2100

Figure 4-4: Hemispherical or regional mean temperature response to transient avia-tion NO, emissions. The Southern Hemisphere (SH) starts experiencing cooling in 1997 while the Northern Hemisphere (NH) warming persists until 2039. The flight corridor (20*N to 60*N) experiences cooling beginning only in 2075.

2000 2020 2040 2060 2080 2100 Year

Figure 4-5: north of 80

Zonal SAT response to constant aviation NOx

0S experience warming in 1992.

emissions. All latitudes 90 N 45 N (D 0 0.04 0.02 0 -0.02 -0.04 -0.06 45S 90S -0.02 -0.04

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0 .0 1 --. . - .. -- .- .--0.01 -0.01 - --0.03 -0.04 -- _{Flight Corridor} - NH -- SH -0.05 ' 2000 2020 2040 2060 2080 2100 Year

Figure 4-6: Hemispherical or regional mean temperature response to constant aviation NO, emissions. The Southern Hemisphere (SH) starts experiencing cooling in 1995 while the Northern Hemisphere (NH) warming persists until 2004. The flight corridor (20'N to 60*N) experiences cooling beginning only in 2030.

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Chapter 5 Temporal Heterogeneity

This chapter discusses the temporal heterogeneity of the climate impact from avia-tion NO, emissions. 03 chemistry in the troposphere is partially driven by photolysis and involves not only NO, but also radicals OH and HO₂, hydrocarbons, carbon monoxide, other trace species [161. 03 production efficiency (OPE), defined as the (net) production of 03 molecules per NO, molecule, varies with background concen-trations. Lin et al. reported that OPE can be as high as 105 at a NO, mixing ratio of 0.4 ppbv when the ratio of non-methane hydrocarbons to NO, is 300 [171. OPE drops to 40 when the mixing ratio of NO, is increased to 1 ppbv for the same scenario. Varying levels of solar radiation intensity also plays a part in affecting OPE. From simulations conducted by Gilmore et al., aviation NO, emitted in October causes 40% more 03 than April [14]

It is unclear whether the CH4 reduction triggered by NO, would exhibit a similar nonlinearity but Fiore et al. reported that the secondary 03 reduction from CH4

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5.1 Radiative Forcing

5.1.1 Global Net Radiative Forcing

Figure 5-1 shows the time progression of global net RF for all 6 scenarios (scenarios 2, 4-8), where emissions are introduced at different times and therefore in different background atmospheric conditions. In all cases, the net RF starts between 31.8 and 43.2 mW/m2 _{in the first year of emissions and decay to a RF between -11.1 and} 0.3 mW/m2 _{65 years after the commencement of emissions. The three simulations} in the high background emissions (EPPA) scenario exhibit a more diverse range of response, as characterized by the wider separation between the curves, whereas the simulations in the mid-range background emissions (RCP 4.5 Similar) scenario have a more closely aligned response. Using the Baseline simulation with mid-range back-ground emissions as the basis for comparison, emissions beginning in 2016 and 2036 with high background emissions result in net RFs that are more than one standard deviation away and are statistically significant. The net RFs of all simulations in the mid-range background emissions and the Baseline scenario in high background emissions become negative in years 24 to 27. The net RFs of simulations with emis-sions beginning in 2016 and 2036 in high background emisemis-sions do not cross into the negative until year 51 and year 61 respectively. Emissions beginning in later years generate higher net RFs than early emissions in each of the background emissions scenarios.

5.1.2 Global 03 Radiative Forcing

The time rate of change of global 03 RFs between simulations in high and mid-range background emissions are distinct 5-2. The former is positive whereas the latter is approximately zero. Averaging the values between years 45 to 65 and normalizing to 1 Tg of NO, emissions, the high background emissions simulations have an 03 RF of 11.8 (Baseline), 14.2 (2016) and 15.4 (2036) mW/M2 _{whereas the simulations with} mid-range background emissions have an 03 RF of 7.7 (Baseline), 8.2 (2016) and

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80_ o Baseline - EPPA 70 a 2016 - EPPA a 2036-EPPA 60 + Baseline - RCP4.5 + 2016 - RCP4.5 50 + 2036 - RCP4.5 4-3 Er20 10 0 -10--20 10 20 30 40 50 60

Year With Emissions

Figure 5-1: The global net RF response to aviation NO, emissions beginning in 1991 (Baseline), 2016 or 2036 with high background emissions (EPPA) or mid-range background emissions (RCP 4.5 Similar). The shaded region illustrates one standard deviation of the Baseline simulation with mid-range background emissions.

8.4 (2036). Using the Baseline simulation with mid-range background emissions as the basis for comparison, the 03 RF of emissions beginning in 2016 with mid-range background emissions begins more than one standard deviation away but realign into the bounds after 50 years of emissions. 03 RFs from all other simulations are more than one standard deviation away. Nonlinearity in global 03 RF exists, possibly a consequence of nonlinearity in OPE.

5.1.3 Global CH

4

Radiative Forcing

As shown in Figure 5-3, the global CH4 RF from all 6 simulations are qualitatively

similar. The CH4 RF starts at -1.1 to -1.2 mW/m2 in the first year and decays to a

value between -58.8 and -44.4 mW/m2 _{after 65 years of emissions. Using the Baseline} simulation with mid-range background emissions as the basis for comparison, CH₄ RFs of all simulations with high background emissions are more than one standard deviation away and are statistically significant.

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70 60 -506 E 4"+ u-30 20- a Baseline - EPPA a 2016 - EPPA a 2036 - EPPA 10- + Baseline - RCP4.5 + 2016 - RCP4.5 + 2036 - RCP4.5 0 10 20 30 40 50 60 Year With Emissions

Figure 5-2: The global 03 RF response to aviation NO. emissions beginning in 1991 (Baseline), 2016 or 2036 with high background emissions (EPPA) or mid-range back-ground emissions (RCP 4.5 Similar). The shaded region illustrates one standard deviation of the Baseline simulation with mid-range background emissions.

5.2 Temperature

In all 6 simulations, aviation NO, emissions result in a cooling SAT response. A maximum warming between 0.001 and 0.006 K exists for all cases. The SAT response has a wider standard deviation than RF responses. Using the Baseline simulation with mid-range background emissions as the basis for comparison, all other simulations are within one standard deviation. There is a lack of evidence to conclude that temporal heterogeneity exists for SAT response from aviation NO, emissions. Simulations at a higher emissions level or a larger ensemble size are needed to improve statistical significance.

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10--20 E~ E LL cc -30 F -40- -50--60 10 20 30 40

Year With Emissions 50 60

Figure 5-3: The global CH4 RF response to aviation NO, emissions beginning in

1991 (Baseline), 2016 or 2036 with high background emissions (EPPA) or mid-range background emissions (RCP 4.5 Similar). The shaded region illustrates one standard deviation of the Baseline simulation with mid-range background emissions.

0.06-0.04 : 0. I--0. -0.04 -0.06 -0.08 10 20 30 40

Year With Emissions 50 60

Figure 5-4: The global SAT response to aviation NO, emissions beginning in 1991 (Baseline), 2016 or 2036 with high background emissions (EPPA) or mid-range back-ground emissions (RCP 4.5 Similar). The shaded region illustrates one standard deviation of the Baseline simulation with mid-range background emissions.

*

Baseline - EPPA * 2016 - EPPA * 2036- EPPA * Baseline - RCP4.5 * 2016 - RCP4.5 * 2036 - RCP4.5 ' a 2aslin - EPPA a 2016 - EPPA + Baseline - RCP4.5 + 2016 - RCP4.5 + 2036 - RCP4.5

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Chapter 6 Conclusion

The aim of this study is to quantify the long-term climate forcing and temperature response of aviation NO, emissions. Additional comparisons between simulations with mid-range and high background emissions shed light on the changes of climate forcing and SAT response from aviation NO. emissions beginning in different years and background atmospheric conditions.

6.1 Transient Emissions

In the simulation with an aviation NO, emissions inventory, the global net RF re-mains positive from 1991 to 2100 with a maximum value of 32.2 (21.4, 41.6) mW/m2 occurring in 2060. The 03 RF approximately scales with emissions at 10 mW/m2 per

Tg emissions while the CH4 RF decreases at a rate higher due to the accumulative

effects from its long lifetime. Focusing on RF only, the positive net RF would imply a warming effect from aviation NO, emissions. However, global SAT is found to de-crease to -0.068 (-0.141, 0.000) K in 2100. This unexpected temperature behavior is attributed to the non-unity efficacies of 03 and CR4.

The zonal RF response is opposite between the Northern Hemisphere and the Southern Hemisphere. The competition between short-lived 03 effect and the ho-mogenous CH4 effect brings the local net RF up to 413.9 mW/m2 _{at 45*N in 2100} while that at 45-S is -170 mW/n2_{. The results would suggest that the Northern}

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Hemisphere would experience increasing warming while the reversed occurs in the Southern Hemisphere. However, owing to differences in climate sensitivity at differ-ent latitudes and heat transport in the ocean, the latitudes that experience warming shrinks over time. All latitudes experience cooling after 2075.

6.2 Constant Emissions

With constant emissions at 4.1 Tg/year, the steady-state net RF is approximately zero. The 0 RF increases over time due to temporal heterogeneity from a varying, high background emissions scenario. The CH4 RF eventually decreases at a rate that

negates the 03 RF. Global SAT response decreases approximately linearly to -0.020 (-0.091, 0.052) K in 2100.

Using the results from two constant emissions simulations, the efficacies of 03 and CH4 are found to be 0.77 and 1.26 respectively. In other words, the cooling effect

from CH4 destruction is 64% more effective in generating a SAT response than the

warming 03. Using the mean and standard deviation of RFs reported by Holmes et al. [251, the probability of aviation NO, being cooling is 67%.

The zonal RF response is stratified by latitude in the Northern Hemisphere with the peak net RF (129 mW/M2_{) occurring at 45*N and that at 86*N oscillates between} 48 and 69 mW/M2_{. The Southern Hemisphere is characterized by zonally similar but} temporally decreasing net RF due to the cumulative effect of CH4. Translating to the

SAT response, one episode of warming above 0.002 K affect the Southern Hemisphere while all latitudes experience cooling after 2030.

6.3 Temporal Heterogeneity

Using aviation emissions beginning in 1991 with mid-range background emissions as a comparison basis, the temporal heterogeneity of RF and SAT responses are assessed. For global net RF, all the test scenarios are within one standard deviation except that of the emissions beginning in 2016 and 2036 with high background emissions. The

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global 03 RF, however, has the most diverse responses. None of the test scenarios is within one standard deviation and the variation is statistically significant. The simulations with high background emissions exhibit an increasing global 03 RF over time while that of mid-range background emissions are approximately constant. A time-varying OPE possibly exists for the high background emissions simulations. For the global CH4 RF, all the simulations are within one standard deviation except that

of the high background emissions. The SAT response has a wider standard deviation than RF responses. There is insufficient statistical significance to indicate temporal heterogeneity in SAT response based on current data.

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