Transcript PPT

Near-term climate forcers and climate policy:
methane and black carbon
Daniel J. Jacob
Atmospheric black carbon: absorber of solar radiation
diesel engines
residential fuel
open fires
freshly emitted
BC particle
Global BC emission [Wang et al., 2014]
Loss of BC is by
wet deposition
(lifetime ~ 1 week)
Gorillas and chimpanzees of climate change
CO2: the 800-lbs gorilla
Methane and BC: the chimps
Do we care about the chimps?
Radiative forcing of climate change
Terrestrial flux
Fout =σ T 4
Solar flux
Fin
• Global radiative equilibrium: Fin = Fout
• Perturb greenhouse gases or aerosols
radiative forcing F = Fin - Fout
• Global equilibrium surface temperature responds as To ~ F
Radiative forcing referenced to emissions, 1750-2011
• Radiative forcing from methane
emissions is 0.97 W m-2, compared to
1.68 W m-2 for CO2
• Radiative forcing from black carbon
aerosol (BC) is 0.65 W m-2, highly
uncertain
• Together methane and BC have
radiative forcing comparable to CO2
• But atmospheric lifetimes of methane
(10 years) and BC (~1 week) are
shorter than CO2 (> 100 years)
• What does that mean for priorities in
controlling future emissions?
[IPCC, 2014]
Climate policy metrics consider the integrated future impact
of a pulse unit emission of a radiative forcing agent
Inject 1 kg of agent X at time t = 0
Concentration C(t) from pulse
time
Impact from pulse = f(C(t))
time
Discount rate

Climate metric =

0
time
(impact)(discount rate)dt
…usually normalized to CO2
Standard IPCC metric: Global Warming Potential (GWP)
Integrated radiative forcing over time horizon [0, H]
Radiative forcing F vs. time
for pulse unit emission of X
at t = 0
CO2 methane BC
H
AGWP(X)   ΔFX (t )dt
0
GWP(X) 
AGWP(X)
AGWP(CO2 )
Discount rate: step function
H
IPCC [2014]
GWP for methane
vs. chosen time horizon:
28 for H = 100 years
 1 Tg CH4 = 28 Tg CO2 (eq)
GWP is easy to compute,
but it does not correspond
to any physical impact
New IPCC metric: global temperature potential (GTP)
Global mean surface temperature change at t = H
CO2 methane BC
GTP ( X ) 
Temperature change vs. time
for pulse unit emission at t = 0
ΔTo , X (H )
ΔTo ,CO 2 (H )
Discount rate:
Dirac function
H
IPCC [2014]
Temperature response
to actual 2008 emissions
taken as a 1-year pulse
Methane as important as CO2
for 10-year horizon, unimportant
for 100-year horizon
Why does methane cause only a short-term temperature response?
Fin
Fout
To
To
t<0
t=0
climate
equilibrium
emission
pulse
F = 0
F > 0
To + To
t = 20 years
climate
response
F < 0
To
t = 100 years
back to
original
equilibrium
F = 0
Simple calculation of Global Temperature Potential (GTP)
Use impulse response function of surface To to pulse F of 1 W m-2 at time t = 0:
0.63
0.43
 To (t )  (
exp[ t / 8.4] 
exp[ t / 410])
8.4
410
t in years
obtained by fitting results of HadCM3 climate model
GTP is then given by
H
To ( H )   F (t ) T ( H  t )dt
0
Boucher and Reddy [2008]
Implication of GTP-based policy for near-term climate forcers
Consider a policy aiming to restrict warming to 2oC in 100 years
Start controlling methane 40 years before target, BC 10 years before target
IPCC [2014]
Controlling methane and BC should be part of climate policy
… but for reasons totally different than CO2
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It addresses climate change on time scales of decades – which we care about
It offers decadal-scale results for accountability of climate policy
It is less sensitive to arguments over what discount rates should be used
It is an alternative to geoengineering by aerosols
It has important air quality co-benefits
BC has additional regional, hydrological impacts
Trend in Arctic sea ice volume
Geoengineering: cloud seeding
Black carbon in the atmosphere
diesel engines
residential fuel
open fires
freshly emitted
BC particle
Global BC emission [Wang et al., 2014]
Loss of BC is by
wet deposition
(lifetime ~ 1 week)
BC exported to upper troposphere is major component of forcing
…because it’s above white clouds instead of dark surface
Integral contribution
To BC forcing
•
• Export to upper
•
deep
troposphere
convection
•
Global mean
BC profile
(chemical
transport model)
•
•
50% from
BC > 5 km
scavenging
•
• •• •
• • • • ••• •
• ••• • • • •
• • •• •
frontal
lifting
BC source
region
(combustion)
BC forcing
efficiency
Ocean
Samset and Myhre [2011]
Multimodel intercomparisons and comparisons to observations
AeroCom
chemical transport models (CTMs) used by IPCC
overestimate BC by order of magnitude in upper troposphere
Pressure, hPa
TC4 aircraft campaign (Costa Rica)
Observed
Models
Such large overestimate must be due
to model errors in scavenging
BC, ng kg-1
Pressure, hPa
HIPPO aircraft campaign over Pacific
obs
models
60-80N
BC, ng kg-1
obs
models
20S-20N
BC, ng kg-1
Koch et al. [2009], Schwarz et al. [2010]
Previous
application
to Arctic
spring (ARCTAS)
BC/aerosol
scavenging
in GEOS-Chem
CTM
Cloud updraft
scavenging
Anvil
precipitation
Large scale precipitation
IN+CCN
CCN+IN,
impaction
entrainment
detrainment
CCN
• Meteorological data including convective mass fluxes
from NASA GEOS assimilation system
• Aerosols are scavenged in cloud by similarity with
condensed water
• Additional scavenging below cloud by rain/snow
• In-cloud scavenging efficiency from freezing/frozen
clouds is highly uncertain
• Additional uncertainty for BC is its efficiency as
cloud condensation nucleus (CCN) and ice nucleus (IN)
BC lifetime in GEOS-Chem is 4 days (vs. 7±2 days in AeroCom models)
GEOS-Chem BC simulation: source regions and outflow
Tests sources, export
Observations (circles) and model (background)
Wang et al., 2014
Normalized mean bias (NMB) in range of -30% to +10%
NMB= -27%
surface
networks
NMB= 6.6%
AERONET BC optical depth NMB= -32%
Aircraft profiles in continental/outflow regions
Asian outflow
HIPPO
US
observed
(A-FORCE)
(HIPPO)
model
(US)
Arctic
(ARCTAS)
NMB= -12%
Comparison to HIPPO BC observations across the Pacific
Model
PDF
PDF, (mg m-3 STP)-1
Observed
• Model doesn’t capture
low tail, is too high at N
mid-latitudes
• Mean column bias is
+48%
• Still much better than
the AeroCom models
Wang et al., 2014
BC top-of-atmosphere direct radiative forcing (DRF)
Absorbing aerosol optical depth (AAOD)
DRF = Emissions X Lifetime X
Mass absorption
Forcing
X
coefficient
efficiency
Global atmospheric load
Emission Global load
Tg C a-1
(mg m-2)
This work 6.5
AeroCom
[2006]
7.8 ±0.4
Bond et al. 17
[2013]
[% above 5 km]
BC
AAOD
x100
Forcing
efficiency
(W m-2/AAOD)
Direct radiative
forcing (W m-2)
fuel+fires
0.15 [8.7%]
0.17
88
0.19 (0.17-0.31)
0.28 ± 0.08
[21±11%]
0.22±0.10 168 ± 53
0.34 ± 0.07
0.55
0.60
0.88
147
• Our best estimate of 0.19 W m-2 is much lower than IPCC recommendation of
0.65 (0.25-1.1) W m-2 or the Bond et al. review
• IPCC value is from models that greatly overestimate BC in upper troposphere
Better understanding of BC scavenging is critical for radiative forcing estimates
Wang et al., 2014