Aviation NOx impact

Climate effects of aviation
NOx: CAM5Chem
Arezoo Khodayari
Chemistry-Climate Working group
March 1, 2012
1
Acknowledgement
Funding Agency: Federal Aviation Administration, Aviation Climate Change
Research Initiative (ACCRI) for support under Contract #: 10-C-NE-UI
amendment 001 and The Partnership for AiR Transportation Noise and
Emissions Reduction (PARTNER)
NCAR Scientists: Dr. Simone Tilmes , Dr. Jean-Francois Lamarque, Dr. Francis
Vitt and Dr. Andrew Gettelman
PhD advisor: Professor Donald Wuebbles
Dr. Seth Olsen and Dr. Kenneth Patten
2
Aviation Climate Effects
Aircraft emissions and climate change
Aviation contributed
approximately 3.5% (5%) of the
total human-made radiative
forcing (RF) on climate for the
year 2005, excluding
(including) effects on cirrus
clouds
Aviation radiative forcing in 2005 [Lee et al., 2009]
3
CAM5chem Study: Climate effects of
aviation NOx Motivation and Objectives
Large uncertainty in the net RF associated with aviation NOx
emissions:
Level of scientific understanding : “medium-low”
Use 3-D Community Earth System Model (CESM) model, CAM5chem to quantify the aviation NOx effects on climate. The results
from this study are going to be further used to update the
representation of aviation NOx effects in SCMs.
4
Relevant Improvements in CAM5chem
• Enhancement in physical parameterizations that makes it
possible to simulate aerosols-cloud interactions such as cloud
droplet activation by aerosol, precipitation processes due to
particle size dependence and explicit radiative interaction of
cloud particles. 3-modal distribution for secondary organic
aerosols and sulphate aerosols, bulk treatment for black
carbon. Addition of Convective Momentum Transport (CMT)
to adjust to the deep convection algorithm, transition to the
finite volume dynamical core.
http://www.cesm.ucar.edu/models/cesm1.0/cam/
5
Model Evaluation
Dynamic Diagnostic Tests
Zonally-averaged CAM5-chem modeled zonal winds compared to ERA40 1980-2001
Reanalysis
Model agrees well
with reanalysis
ERA-40: reanalysis of
meteorological observations
from September 1956 to August 2002,
conducted by the European Centre for
Medium-Range Weather Forecasts
6
Model Evaluation
Dynamic Diagnostic Tests
CAM5-chem modeled zonally-averaged temperatures compared to AIRS IR 2002-06
Sounder
Model agrees well
with reanalysis
7
Model Evaluation
Chemistry Diagnostic Tests
CAM5-chem modeled O3 compared seasonally to O3 sondes data for Ascension,
Boulder and Broadmeadows stations
O3 profiles are well reproduced
8
2006 Aircraft Emission Inventory
Regional mass distributions of aviation NOx emissions
1o latitude by 1o longitude by 150 m
NOX emission (Tg)
x 10
1
90
-4
0.9
60
0.8
0.7
latitude
30
0.6
0
0.5
0.4
-30
0.3
Total: 2.7Tg (NO2)/yr
-60
0.2
0.1
-90
0
60
120
180
longitude
240
300
360
0
9
Simulations
5 years spin up to get the chemistry right
Two 10-year simulations: one simulation considered all NOx emissions
including aviation NOx, and the other simulation had no aviation NOx
Aviation Climate Change Research Initiative year 2006 hourly emissions
1.9o lat ×2.5o lon, 30 levels, top ~ 40 km
Mode: specified dynamics; Present day CAM5 climatology
Specified dynamic mode advantages over a free mode:
(1) possible to pick out aviation signal
(2) consistent simulations between the two runs
(3) calculated effects are just due to the changes in chemistry and are not
impacted by the changes in dynamic
10
Monthly Zonal Mean Perturbations of NOx
(pptv) Caused by 2006 Aviation NOx Emissions
zonal NOx (ppt), July
200
50
300
45
40
Pressure (hPa)
400
35
500
30
600
25
20
700
15
800
10
900
5
0
1000
90S
60S
30S
EQ
latitude
30N
60N
90N
zonal NOx (ppt), January
80
200
300
60
Pressure (hPa)
400
40
500
600
20
700
0
800
-20
900
1000
90S
60S
30S
EQ
latitude
30N
60N
90N
At high altitude:
*more actinic flux at high latitude,
more O(1D) to oxidize H2O and produce OH
*Higher OH in July
NO2 + OH + M → 2 HNO3 + M
=>Less NOx perturbation compared to Jan
Near the surface:
* ozone perturbation propagated to the surface can react
with background NOx
*less actinic flux at high latitude in Jan, less photolysis of NO3
back to NO2
NO2 + O3 → NO3
NO3 + NO2 → N2O5
More aerosols near the surface and between 30-60o N;
heterogeneous reactions on aerosols:
N2O5 → 2 HNO3
=> Higher decrease in pre-existing NOx
NO3 → HNO3
compared to July
NO2 → 0.5 * (OH + NO + HNO3)
11
Monthly Zonal Mean Perturbations of NOx (%)
Caused by 2006 Aviation NOx Emissions
Change in zonal NOx (%), July
200
70
300
60
Pressure (hPa)
400
50
500
40
600
30
700
20
800
10
900
1000
90S
0
60S
30S
EQ
latitude
30N
60N
90N
Change in zonal NOx (%), January
Pressure (hPa)
• Lower background NOx at the cruise
altitude in January as air is more stable
=>higher aviation perturbation relative to
background
200
450
300
400
400
350
300
500
• Higher background NOx near the surface in
January which makes it hard to see the NOx
decrease near the surface in a relative term,
but it was noticeable in previous slide
(absolute change in NOx)
250
600
200
700
150
800
100
900
50
1000
90S
0
60S
30S
EQ
latitude
30N
60N
90N
12
Yearly Mean Perturbations of Ozone Column (∆DU,
Change in Ozone in Dobson Units) due to 2006
Aviation NOx
Map of yearly mean columnar ozone perturbation (%)
1
90
0.9
60
0.8
0.7
latitude
30
0.6
0
0.5
Peroxy radicals (RO2 and HO2) produced
through CO and VOC oxidation react with
NO:
HO2+NO
NO2 +hv
O+ O2+ M
0.4
-30
0.3
-60
-90
OH+NO2
NO + O
O3+ M
0.2
0.1
0
60
120
240
180
longitude
300
360
Dobson Unit (DU) that is a measure of the
columnar density of ozone overhead.
maximum of 1% change in
columnar ozone that is
equivalent to 2.5 Dobson Unit
change in column O3
13
Annual Average Zonal Mean Perturbations of Ozone
(ppbv) Caused by 2006 Aviation NOx
Annual mean zonal ozone (ppb)
200
Aviation contribution in annual mean zonal ozone (%)
9
200
5
400
7
6
600
5
4
800
3
2
4
Pressure (hPa)
Pressure (hPa)
8
400
3
600
2
800
1
1
1000
90S 60S 30S EQ 30N 60N 90N
latitude
1000
90S 60S 30S EQ 30N 60N 90N
latitude
Maximum north of 30oN and between 200-300 hPa where most of the flights operate.
Maximum change in zonal mean ozone concentration of about 10 ppbv that corresponds
to about a 5% of background O3.
14
Monthly Zonal Mean Perturbations of Ozone
(ppbv, %) Caused by 2006 Aviation NOx Emissions
Change in zonal ozone (%), July
Change in zonal ozone (%), January
7
7
200
200
6
400
5
500
4
600
3
700
2
800
1
900
1000
90S
60S
30S
EQ
30N
latitude
60N
90N
0
6
300
Pressure (hPa)
Pressure (hPa)
300
400
5
500
4
600
3
700
2
800
1
900
1000
90S
60S
30S
EQ
latitude
30N
60N
90N
0
O3 reach a maximum of about 5% change in July and a maximum of about 7%
change in January.
Higher in July in relationship to the available sunlight for photochemistry.
15
Annual Average Zonal Mean Perturbations of OH
and HO2 (∆molecules/cm3) Caused by 2006 Aviation
NOx Emissions
Aviation contribution in annual mean zonal OH (10 4 ∆molecules/cm3)
200
300
OH
18
16
14
Pressure (hPa)
400
12
500
10
600
8
700
6
800
4
900
1000
90S
2
0
60S
30S
EQ
latitude
30N
60N
90N
Aviation contribution in annual mean zonal HO2 (104 ∆molecules/cm3)
200
300
700
OH2
600
Pressure (hPa)
500
400
400
500
300
600
200
100
700
0
800
-100
900
1000
90S
-200
-300
60S
There is up to 27% increase in OH relative to
background (∼3 times the O3 perturbation)
30S
EQ
latitude
30N
60N
90N
There is an increase in OH at cruise altitude:
O2 +O(1D)
O3+hv
O(1D) + M
O+M
O(1D) + H2O
2OH
Increase in OH below cruise altitude due to
O3 transport
and decrease in HO2 at cruise altitude:
dominant reaction:
HO2 + NO
OH + NO2
and increase in HO2 below cruise altitude
due to higher H2O mixing ratio and higher
produced OH, and higher tropospheric CO
and VOC that reacts with OH and through
oxidation result in higher HO2
16
Monthly zonal mean perturbations of OH
(∆molecules/cm3) caused by 2006 aviation NOx
zonal OH (104 ∆molecules/cm3), January
zonal OH (104 ∆molecules/cm3), July
200
200
25
25
300
300
20
500
15
600
700
10
20
400
Pressure (hPa)
Pressure (hPa)
400
500
15
600
700
10
800
800
5
5
900
900
1000
90S
60S
30S
EQ
latitude
30N
60N
90N
1000
90S
0
60S
30S
EQ
latitude
30N
60N
90N
0
zonal HO2 (104 ∆molecules/cm3), January
zonal HO2 (104 ∆molecules/cm3), July
100
200
200
2500
50
300
300
0
2000
400
1500
500
600
1000
700
Pressure (hPa)
Pressure (hPa)
400
-50
500
-100
600
-150
700
-200
500
800
800
0
900
1000
90S
60S
30S
EQ
latitude
30N
60N
90N
-500
-250
900
1000
90S
-300
60S
30S
EQ
latitude
30N
60N
90N
-350
17
Changes in Methane Lifetime due to Aviation
NOx Emissions
(1) find the change in methane concentration using Fuglestvedt et al. [1999] equation :
[CH4]ss = [CH4]ref × (1-1.4×∆τ0/∆τref)
where ∆τ0 = ∆τper - ∆τref
[CH4]ref: global annual mean methane concentration in reference run with no perturbation
[CH4]ss: steady state global annual mean CH4 concentration due to perturbation
Pressure (hPa)
Perturbation in zonal annual mean CH4 (ppb)
200
-38
300
-38.5
-39
400
-39.5
500
-40
600
-40.5
700
-41
800
-41.5
900
-42
1000
90S
1.64% decrease in CH4 lifetime
due to the year 2006 aviation
NOx emissions
60S
30S
EQ
latitude
30N
60N
Hoor et al. [2009] reported
1.04(±0.40)% decrease in CH4
lifetime due to the year 2000
aviation NOx emissions
90N
18
Key Findings
o Maximum change of about 55 ppt in zonal mean NOx in July and about 80
ppt in Jan
o Up to 40 ppt decrease in NOx near the surface between 30-60o N in Jan
o Maximum annual mean zonal ozone increase of ~ 5.2% (~ 9 ppb)
o 4.8% in CAM4chem
o ~ 10 ppb for 7.3 Tg NO2 in the year 2050 from Sovde et al. [2007]
o ~ 7% for 7 Tg NO2 in the year 2050 from Grewe et al. [1999]
o Maximum annual mean zonal OH increase of ~ 27%
o 1.64% decrease in CH4 lifetime, excluding CH4 feedback on its lifetime;
1.04(±0.40)% decrease in Hoor et al. [2009] study; in response to 2.2 Tg NO2
o 1.3(±0.30)% decrease in Hodnebrog et al. [2011] study; in response to 2.7 Tg
NO2
19