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

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

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]

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

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

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)

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

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

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

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, 20-30 d for 7Be

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

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

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]

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]

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

“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

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

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

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

Two-way air-sea exchange of acetone