Climate Impact of Aviation NOx Emissions:
Radiative Forcing, Temperature, and Temporal
Heterogeneity
by
U
S
MASUA
OF TECHNOLOGY
Lawrence Man Kit Wong
OCT 0
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
August 21, 2014
Signature redacted
Certified by ..........
.......................
Steven R. H. Barrett
Associate Professor of Aeronautics and Astronautics
Thesis Supervisor
Signature redacted-
...........
Paolo C. Lozano
Associate Professor of Aeronautics and Astronautics
Chair, Graduate Program Committee
Accepted by .............
2 201
)
r..
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 CH 4 , 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). However, 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 system 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 CH 4 efficacies.
3
Comparing simulation results from six different scenarios, varying degrees of temporal 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
Title: Associate Professor of Aeronautics and Astronautics
4
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 encouragement 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.
John 15:13
5
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6
Contents
1 Introduction
15
2 Methods
17
Emissions Scenarios ................
. . . . . . . . . . . . . . .
17
2.1.1
Aviation Emissions .........
. . . . . . . . . . . . . . .
18
2.1.2
Anthropogenic Emissions ......
. . . . . . . . .. . . . ...
19
. . . . . . . . . . . . . . .
21
. . . . . . . . . . . . . . .
22
2.2
Integrated Global System Model (IGSM)
2.3
Ensemble Simulation ..............
.
2.1
3 Radiative Forcing
3.2
Global- Mean RF Response . . . . . . . .
. . . . . . . . . . . . . . .
24
3.1.1
Transient Aviation NO, Emissions
. . . . . . . . . . . . . . .
24
3.1.2
Constant Aviation NO, Emissions.
. . . . . . . . . . . . . . .
24
Zonal Mean RF Response .........
. . . . . . . . . . . . . . .
26
3.2.1
Transient Aviation NO, Emissions
. . . . . . . . . . . . . . .
26
3.2.2
Constant Aviation NO, Emissions. . . . . . . . . . . . . . . .
26
.
3.1
23
4 Temperature
4.1
4.2
29
Global Mean SAT Response ........
. . . . . . . . . . . . . . .
30
4.1.1
Transient Aviation NO, Emissions
. . . . . . . . . . . . . . .
30
4.1.2
Constant Aviation NO, Emissions.
. . . . . . . . . . . . . . .
30
4.1.3
Efficacies ...................
. . . . . . . . . . . . . . .
31
. . . . . . . . . . . . . . .
32
Zonal Mean SAT Response .........
7
. . . . . . . . . . . . . .
32
4.2.2
Constant Aviation NO, Emissions . . . . . . . . . . . . . . .
33
.
.
Transient Aviation NO, Emissions
37
Temporal Heterogeneity
5.2
. . . . . . . . . . . . . . . . .
38
5.1.1
Global Net Radiative Forcing . . . . . . . . . . . . . . . . .
38
5.1.2
Global 03 Radiative Forcing.
. . . . . . . . . . . . . . . . .
38
5.1.3
Global CH4 Radiative Forcing . . . . . . . . . . . . . . . . .
39
. . . . . . . . . . . . . . . . .
40
.
.
.
Radiative Forcing ...........
.
5.1
Temperature. ................
.
5
4.2.1
43
6 Conclusion
6.1
Transient Emissions. ............................
43
6.2
Constant Emissions ..................................
44
6.3
Temporal Heterogeneity
.........................
8
44
List of Figures
2-1
The transient (scenario 1) aviation NO, emissions profile. The proffile
assumes 88% of NO, is emitted as NO. . . . . . . . . . . . . . . . . .
2-2
19
The spatial configuration of aviation NO, emissions. The bulk of the
emissions are centered just below the tropopause of the northern hemisphere. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Comparison of anthropogenic emissions of species relevant to NO.-0 3
-
2-3
20
CH4 reactions between the EPPA-generated emissions scenario (high
greenhouse gases emissions) and RCP 4.5 Similar (mid-range RF stabilization scenario). . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-1
21
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. . . . . . . . . . . . . . .
3-2
03
RF response to transient aviation NO., emissions in comparison
with emissions profile.
3-3
24
. . . . . . . . . . . . . . . . . . . . . . . . . .
25
RF response to constant aviation NO, emissions (on an NO 2 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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3-4
25
Zonal RF response to transient aviation NO, emissions. At 45*N in
2100, net RF reaches 206.7 mW/m 2 (a); 03R F reaches 719.2 mW/M 2
(b); CH4 RF reaches -242.5 mW/m2 (c).
9
. . . . . . . . . . . . . . . .
27
3-5
Zonal RF response to constant aviation NO, emissions. At 45*N in
2100, net RF reaches 129 mW/m 2 (a); 03 RF reaches 206.7 mW/M 2
(b); CH4 RF reaches -60.9 mW/M 2 (c) . . . . . .
4-1
. . . . . . . . . . .
28
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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4-3
Zonal SAT response to transient aviation NO, emissions. The majority
of the latitudes experience mild warming in 1992.
4-4
31
. . . . . . . . . . .
33
Hemispherical or regional mean temperature response to transient aviation 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.
4-5
. . . . . . . . . . . . . . . . . . . . .
Zonal SAT response to constant aviation NO, emissions. All latitudes
north of 80 *S experience warming in 1992. . . . . . . . . . . . . . . .
4-6
34
34
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.
5-1
. . . . . . . . . . . . . . . . . . . . .
35
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.
10
. . . . . . . . . . . . . . . . .
39
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.
5-3
.................
40
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 midrange background emissions. ........................
11
41
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12
List of Tables
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.
13
. . . . . . . .
18
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14
Chapter 1
Introduction
Nitrogen monoxide (NO) and nitrogen dioxide (NO 2 ) (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 CH 4 [3].
Comparing to the one-year timescale of inter-
hemispheric mixing, the effect of the 03 formation on radiative imbalance is shortlived (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 NO 2 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
15
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 temperature 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 simulations. 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.
16
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 included) scenarios are used. Each scenario is analyzed through a 400-member ensemble
simulation to determine the mean climate forcing and temperature response. Interscenario 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.
17
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
4
Constant at 2016 rate; introduced in 2016
EPPA
5
Constant at 2016 rate; introduced in 2036
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 emissions. 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,
18
3
0r
25-
20-
15-
S100
x
5-
0
2000
2020
2040
Year
2060
2080
2100
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 nonaviation emissions because of the potential for interactions between the 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
19
1.8
100
200
1.4
300
CU
CU
400
CU
500
600
0.8
700
0.6
a)
800
0.4
M
900
0.2 0-
1000
90S
L
45S
0
Latitude
45 N
90 N
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 values that mimic RCP 4.5, which we term RCP 4.5 Similar.
Figure 2-3 compares
the emissions levels of species relevant to NO,-0 3 -CH 4 reactions. When compared
with the RCP scenarios, the EPPA-derived CO 2 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/m 2 by 2100. We observe that CH 4 emissions are higher in the EPPAgenerated 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
20
higher NO, emissions in the EPPA-generated scenario also lead to a different ozone
production efficiency between the two groups of simulations [17].
1
4
80
60
0.8
3
0~
0~
N
0
0
40
0
2
20
2000
2050
Year
2
200
1 50
0
05;;P0
02000
CUD
2050
Year
2100
0.6
0.4
2000
2100
300
0
Z 100
I
0
2050
Year
2100
1 00
502000
2050
Year
0.22000
2050
Year
2100
--
EPPA
-
RCP 4.5 Similar
2100
-
Figure 2-3: Comparison of anthropogenic emissions of species relevant to NO2-0 3
CH 4 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 incorporates a coupled atmosphere-ocean-land model linked to other models that simulate
climate-relevant processes. The anthropogenic and natural emissions drive the coupled atmospheric chemistry and climate models. The outputs then determine water
and energy budgets, C0 2 , CH 4 , and N2 0 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
21
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 CH 4 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].
22
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/M 2 [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
and long-lived 03 effects -6.6
9.7 mW/m2 , long-lived CH4 effects -16.1
3.3 mW/m2
23
5.6 mW/M 2
,
effects was found to be 27.3
3.1
3.1.1
Global Mean RF Response
Transient Aviation NO, Emissions
In scenario 1, the net global average RF reaches a maximum of 32.2 mW/m 2 (10year rolling average, 15-85% confidence interval (21.4, 41.6) mW/m 2 ) 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
-
2000 2010
0 -CH
3
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/m 2 in 1991 to
approximately zero beginning in 2014 (0.314 (-10.3, 10.2) mW/M 2 ) (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/M 2 in 2100. The CH4 RF begins at -1.10 (-1.40, 0.00) mW/M 2 in 1991 and
decreases, reaching the same magnitude of the 03 RF beginning in 2013.
24
30
300
NOXemission rate
-
..25 --
NOX-03 RF
250
20-
- 200 M
15 -
-150
0
E
c
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 00 - -
..... .......... ........
-
........
-
60
- .
..
....
20
E
LL
O
-20- 40 -...
.
-.. ...
. ...... .. ....
.... ..
.
z
.
--.....
- 60 -.. .
- 80 -
.- .
-- 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 NO 2 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/m 2 and
that of CH4 is -14.5 (-15.0, -14.0) mW/m 2 (average between 2080 and 2100). These
25
values are within the bounds reported by Lee et al. and Holmes et al.
3.2
3.2.1
Zonal Mean RF Response
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 CH 4 . 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/m 2 in 2030
and reaches 719.2 mW/m2 in 2100. The CH 4 RF values are more zonally homogenous.
At the same latitude, the CH 4 RF is -0.9 mW/m 2 in 1991, decreases to -48.7 mW/m 2
in 2030 and reaches -242.5 mW/m 2 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 CH 4 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/m 2 ) while
the net RF at 86*N oscillates between 48 and 69 mW/m 2 . 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/m 2 , 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 CH 4 RF starts at -2.0 mW/m 2 , decreases to -43.1 mW/m 2 in 2030
and reaches -60.9 mW/m 2 in 2100.
26
a. Net RF (mW/m2)
700
90 N
45 N
0
600
0
45S
90 S
500
2000
2020
2060
2040
2080
2100
400
)
b. 0, RF (mW/m 2
90 N
300
45 N
0
(U
0
200
-J
45S
90S
2000
2020
2060
2040
2080
2100
100
C. CH 4 RF (mW/m2)
90 N
0
45 N
.0
-100
0
45S
-200
90S
;uuu
zubu
ZU4U
2100
Year
Figure 3-4: Zonal RF response to transient aviation NO, emissions. At 45*N in 2100,
net RF reaches 206.7 mW/m 2 (a); 03 RF reaches 719.2 mW/M 2 (b); CH 4 RF reaches
-242.5 mW/m 2 (c).
27
)
a. Net RF (mW/m 2
200
90 N
45 N
0
45S
90 S
150
2000
2020
2060
2040
2080
2100
b. 03 RF (mW/m2)
90 N
100
45 N
0
45S
90S
50
dUUU
2uzu
2U4U
zubu
2odU
2100
)
C. CH4 RF (mW/m 2
90 N
0
45 N
0
45S
-50
90S
2000
2020
2040
2060
2080
2100
Year
Figure 3-5: Zonal RF response to constant aviation NO. emissions. At 45'N in 2100,
net RF reaches 129 mW/M 2 (a); 03 RF reaches 206.7 mW/m 2 (b); CH 4 RF reaches
-60.9 mW/m 2 (c).
28
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 atmosphereocean 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 precludes the use of large ensemble simulations. Olivi6 et al. used a 3-member AOGCM
simulations to predict the SAT response of non-CO 2 effects from aviation (which include 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].
29
4.1
4.1.1
Global Mean SAT Response
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
-
-0.050
-0.1
-
-0.15
-0.2-
.
....
-0.25-
-
2000 2010 2020 2030 2040 2050 2060
Year
2070 2080 2090 2100
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
30
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 nonunity 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 CH 4 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
31
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
SATs 2
RFo,s2
RFCH4 ,S2
A0 3
SATs3
RF0 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 steadystate 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 CO 2 [4, 32].
The efficacy of aviation NO-induced CH 4 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 CH 4 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
4.2.1
Zonal Mean SAT Response
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
32
I
90 N
0
45 N
-0.05
-0.15
45S
-0.2
90S
2000
2020
2040
Year
2060
2080
2100
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.
33
0.02r
0
-0.02
-0.04
-0.06
-0.08-0.1
-0.12
-
Flight Corridor
-NH
-SH
-0.14
2000
2020
2040
Year
2060
2080
2100
Figure 4-4: Hemispherical or regional mean temperature response to transient aviation 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.
90 N
0.04
0.02
45 N
0
(D
0
-0.02
-0.04
45S
-0.06
90S
2000
2020
2040
Year
2060
2080
2100
Figure 4-5: Zonal SAT response to constant aviation NOx emissions. All latitudes
experience warming in 1992.
north of 80
0S
34
0 .0 1 -
-
.
-.
-.-...
-0.01
-
-
-
-0.01
-0.03
-0.05
Flight Corridor
--
-
NH
--
SH
'
-0.04
2000
2020
2040
Year
2060
2080
2100
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.
35
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36
Chapter 5
Temporal Heterogeneity
This chapter discusses the temporal heterogeneity of the climate impact from aviation NO, emissions. 03 chemistry in the troposphere is partially driven by photolysis
and involves not only NO, but also radicals OH and HO 2 , 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 concentrations. 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
destruction is approximately linear up to 430 Tg CH4 per annum [3].
37
5.1
5.1.1
Radiative Forcing
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 background 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 emissions beginning in 2016 and 2036 in high background emissions 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/M 2 whereas the simulations with
mid-range background emissions have an 03 RF of 7.7 (Baseline), 8.2 (2016) and
38
80_
o
Baseline - EPPA
70
a 2016 - EPPA
a 2036-EPPA
60
+ Baseline - RCP4.5
+ 2016 - RCP4.5
50
+ 2036 - RCP4.5
43
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 CH4 Radiative Forcing
As shown in Figure 5-3, the global CH 4 RF from all 6 simulations are qualitatively
similar. The CH 4 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/m 2 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.
39
-
70
-
60
506
E 4"+
u-30
20100
10
20
30
40
Year With Emissions
a
a
a
+
Baseline - EPPA
2016 - EPPA
2036 - EPPA
Baseline - RCP4.5
+
+
2016 - RCP4.5
2036 - RCP4.5
50
60
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 background 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.
40
*
*
*
*
*
*
10-
Baseline - EPPA
2016 - EPPA
2036- EPPA
Baseline - RCP4.5
2016 - RCP4.5
2036 - RCP4.5
-20
E~
E
-30 F
LL
cc
-40-
-60
'
-50-
10
20
30
40
Year With Emissions
50
60
Figure 5-3: The global CH 4 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.
0.060.04 :
0.
I-
-0.
-0.04
a 2aslin - EPPA
a 2016 - EPPA
-0.06
-0.08
+ Baseline - RCP4.5
+ 2016 - RCP4.5
+ 2036 - RCP4.5
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 background emissions (RCP 4.5 Similar). The shaded region illustrates one standard
deviation of the Baseline simulation with mid-range background emissions.
41
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42
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 remains positive from 1991 to 2100 with a maximum value of 32.2 (21.4, 41.6) mW/m 2
occurring in 2060. The 03 RF approximately scales with emissions at 10 mW/m 2 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 decrease to -0.068 (-0.141, 0.000) K in 2100. This unexpected temperature behavior is
.
attributed to the non-unity efficacies of 03 and CR 4
The zonal RF response is opposite between the Northern Hemisphere and the
Southern Hemisphere. The competition between short-lived 03 effect and the homogenous 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/n 2 . The results would suggest that the Northern
43
Hemisphere would experience increasing warming while the reversed occurs in the
Southern Hemisphere. However, owing to differences in climate sensitivity at different 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
CH 4 are found to be 0.77 and 1.26 respectively. In other words, the cooling effect
from CH 4 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/M 2 ) occurring at 45*N and that at 86*N oscillates between
48 and 69 mW/M 2 . 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
44
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.
45
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46
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