1. Emission and deposition processes (Brasseur and Jacob, chapters 8 and 9)

2. Sources contributing to global emissions
NOx
CO2, NOx, soot
Lightning
Aircraft
CO2,, SO2,
ash
CO2, CO, VOCs
NOx, SO2, soot,
OA, metals
CH4,
NH3, N2O
Sea salt
VOCs
Sulfides
CO2, CO, VOCs
NOx, NH3, OS, soot
CO2, VOCs
N2O, NOx
Fuel combustion
& industry
Open fires
Terrestrial
biosphere
Agriculture
Volcanoes
Ocean
VOCs = volatile organic compounds
OA = organic aerosol

3. Construction of emission inventories
“Bottom-up” knowledge of processes driving emissions
Activity rate
Emission factor
Scale factor
emission flux
of species i
Anthropogenic NOx emissions for 2013 [Keller et al., 2014]

4. Atmospheric observations as top-down constraints on emissions
Aircraft data over eastern US [Hudman et al., 2008]
Model CO (ppb)
US EPA
CO emissions
EPA emissions
reduced by 60%
Observed CO (ppb)
Observed CO (ppb)
Bayesian inverse analyses blend error-weighted bottom-up and top-down information:
Bottom-up prior estimate
EA ± σA
Model concentrations
nM ± σM
Observed concentrations
nO ± σO
Bayesian optimization
Posterior emission estimate
E ± σ

5. Deposition processes Wet deposition (scavenging) In-cloud scavenging
(rainout)
Below-cloud scavenging
(washout)
Dry deposition
Bi-directional exchange
SEA/LAND

6. Scavenging of gases by liquid clouds and rain
Consider equilibrium
where X(aq) includes all dissolved species in fast equilibrium. Define effective Henry’s law constant
Then the fraction f of X incorporated into the liquid phase is
where nX is the concentration in moles per liter of air and L is the liquid water content (volume water per volume of air)

7. Effective Henry’s law constants and gas-cloud partitioning
Species
KH*, M atm-1
(pH=4.5, T=280K) O3
1.8x10-2
PAN
1.1x101
CH3OOH
9.5x102
CH2O
1.4x104
H2O2
4.1x105
NH3
5.0x106
HNO3
4.3x1011
mostly in gas
mostly in cloud
(L ~ 10-7 v/v)
Most gases are either very efficiently scavenged (KH* >> 104 M atm-1)
or negligibly scavenged

8. ATMOSPHERIC AEROSOL: suspension of condensed-phase particles in air
number
Typical aerosol size distribution
surface
volume
Aerosols are the visible part of the atmosphere:
California fire plumes
Pollution off U.S. east coast
Dust off West Africa

9. Aerosol wet scavenging processes
CCN activation
coalescence
diffusion
interception
impaction
raindrop
interception
diffusion
impaction

10. Inference of aerosol lifetimes from 222Rn-210Pb-7Be system
cosmic
rays
STRATOSPHERE
decay
7Be
aerosol
TROPOSPHERE
53 d
deposition
decay
222Rn
210Pb
aerosol
5.5 d
23 y
deposition
SOIL
Knowledge of
222Rn emission, 7Be source
Tropospheric masses of 210Pb, 7Be
226Ra
222Rn
2,300 y
Lifetimes against deposition
of 7-10 d for 210Pb, d for 7Be

11. Scavenging processes in convective updrafts
Model intercomparison
deep convective outflow
OUTFLOW
H2O2
Cold cloud:
co-condensation, surface uptake,
aerosol scavenging?
precipitation
HNO3
Riming mixed cloud:
retention efficiency
upon drop freezing?
ENTRAINMENT
Warm cloud:
scavenging relatively
well understood:
Henry’s law for gases
Collision with spherical drops for aerosols
Barth et al. [2007]
INFLOW:
soluble gases
and aerosols

12. 1750-present radiative forcing of climate (IPCC, 2014)
Large positive forcing
from black carbon (BC)

13. Integral contribution
Small BC fraction exported to the free troposphere is major component of BC direct radiative forcing
Integral contribution
To BC forcing
Global mean
BC profile
(Oslo CTM) • • •
Export to free
troposphere
deep
convection
BC forcing
efficiency • •
50% from
BC > 5 km •
scavenging • • • •
frontal
lifting • • • • • • • • • • • • • • • • • • • • • • • •
BC source
region
(combustion)
Ocean
Samset and Myhre [2011]

14. Free tropospheric BC in standard models is ~10x too high
Multimodel intercomparisons and comparisons to observations
Multimodel intercomparison and comparison to observations
Free tropospheric BC in standard models is ~10x too high
This has major implications for IPCC radiative forcing estimates
TC4 (Costa Rica, summer)
Observed
Models
Pressure, hPa
Large overestimate must reflect
model errors in scavenging
BC, ng kg-1
HIPPO over Pacific (Jan)
Pressure, hPa
obs
models
20S-20N
obs
models
60-80N
BC, ng kg-1
BC, ng kg-1
Koch et al. [2009], Schwarz et al. [2010]

15. Modeling dry deposition: turbulent flow over flat surface
mean wind
Turbukent diffusion
u = 0 at z= zo,,m (roughness height)
quasi-laminar flow for z < zo,m
FLAT ROUGH SURFACE
Friction velocity
where Fm is the surface momentum flux

16. “Big-leaf” concept for dry deposition
Measurement altitude
or midpoint of lowest model level
n(z1)
turbulence
Conserved flux
from z1 to leaf surface
Zero-momentum point z0,m where turbulence dies
n(z0,m)
molecular diffusion
n(z0,c)
Leaf surface
uptake and reaction
“Big leaf”
(canopy element)
Leaf interior
n = 0

17. Big-leaf resistance-in-series model for dry deposition
Deposition flux F = -V(z1)n(z1)
where deposition velocity V (z1) = 1/(RA(z1) + RB,i + RC,i)
d is a displacement height to account for the canopy

18. July mean deposition velocities of ozone and nitric acid
O3: limited by surface resistance HNO3: limited by aerodynamic resistance

19. Bi-directional exchange
Air resistance RA
nA(0)
ATMOSPHERE
SEA
nS(0)
Sea resistance
RS = f(U)
“Inverse” dimensionless
Henry’s Law constant
H = nA(0)/nS(0)
bulk nS
exchange
velocity
Net deposition flux

20. Two-way air-sea exchange of acetone