aerosols and the climate system - cnr · 2012-07-05 · aerosols and the climate system peter j....

Aerosols and the Climate System

Peter J. Adams

Center for Atmospheric Particle Studies (CAPS)

Department of Civil and Environmental Engineering

Department of Engineering and Public Policy

Carnegie Mellon University

Alpine Summer School: Climate, Aerosols, and the Cryosphere

20 June 2012

Outline

• Introduction and Overview

• Aerosols: Size, Chemistry, Behavior

• Aerosol Climate Impacts

• Bigger Picture Context

• Aerosols: a major uncertainty in climate science

• Research Challenges

• (Aerosol Properties)

• Mie theory: optics; aerosol-sunlight interactions

• Kohler theory: aerosol-cloud interactions

Atmospheric Particles (“Aerosols”)

SEM Images: Pittsburgh Air Quality Study Gary Casuccio, R.J. Lee Group, Monroeville, PA

Small Suspended Particles -- few nm to 10s mm -- Complex shapes -- >1000s compounds -- Multiphase -- Many sources

Diesel Soot

1 mm1 mm1 mm1 mm

Coal Combustion

0.2 μm0.2 μm0.2 μm

Biological

Introduction

• Formation mechanisms • Primary: particles directly emitted by a source (e.g. smoke from

combustion)

• Secondary: gas-phase oxidation products that form particles

• Composition • Wind-blown: Mineral dust, sea spray

• Combustion: elemental and organic carbon

• Atmospheric chemistry: sulfate, nitrate, secondary organic carbon

• Size • Diameters are ~1 nm to ~10 mm

• Most behavior is size-dependent

• Growth by condensation and coagulation important

Atmospheric Particles: A Primer

Nucleation Mode

(1-10 nm)

Ultrafine Mode

(10-100 nm)

«Aitken» mode

Fine Mode

(0.1-1 mm)

«Accumulation»

Coarse Mode

(1-10 mm)

Cloud Drops

(10+ mm)

Nuc Mode

(1-10 nm)

UF Mode

(10-100 nm)

Fine Mode

(0.1-1 mm)

Coarse Mode

(1-10 mm)

Cloud Drops

(10+ mm)

10 nm 100 nm 1 mm 1 nm 10 mm

contributes most to aerosol

number concentrations

surface area

mass conc.

always when present when present

Sources of Particles

• Wind-blown

• Primary (directly emitted) particles

• Sea-salt and mineral dust

• Larger than 1 mm (mostly)

• Aerosol nucleation (new particle formation)

• Clustering of supersaturated gases to form particles

• Secondary particle formed in atmosphere from

precursors: H2SO4(g) (...and other species)

• Smallest identifiable «particle» is 1 nm

• Combustion

• «Primary» particle directly emitted by a source

• ...really nucleation in or near source

• Sizes typically 30-300 nm

Nuc Mode

(1-10 nm)

UF Mode

(10-100 nm)

Fine Mode

(0.1-1 mm)

Coarse Mode

(1-10 mm)

Cloud Drops

(10+ mm)

ation combustion

Knudsen Number

• Continuum regime (Kn << 1; coarse mode)

• air may be treated as a continuum (standard fluid

dynamics and mass/heat transport)

• Transition regime (Kn ~ 1; fine mode)

• empirical correction factors

• Kinetic regime (Kn >> 1; ultrafine mode)

• particles small → kinetic theory of gases

Dp: Particle

diameter

l : Mean free path

of air molecules pD

Condensation: Kinetic Regime

spk cccRJ 2

Particle

Condensing Gas Jk: Net flux to one

particle

(condensation

minus evaporation)

: accomodation

coefficient

Rp: Particle radius

: Mean velocity of

condensing gas

: bulk

concentration of

condensing gas

cs: “surface”

(equilibrium)

concentration of

condensing gas

cflux (per unit area) particle cross

sectional area

Comments:

•J is condensation rate to particle (molecules s-1)

•J ~ Rp2 in kinetic regime

Condensation: Continuum Regime

• Diffusive flux from bulk gas to particle surface

(or vice versa) governs transport

• Since flux per area ~ 1/Rp, overall condensation

rate is ~Rp (not Rp2)

Particle )(4 sgpc CCDRJ

Jc = (diffusive flux per area)(surface area) ~ Rp2 (?)

Fick’s Law: (diffusive flux per area)

L (thickness of

diffusive layer)

Condensation: Particle Growth Rates

• More useful to think about particle growth rates

• GR = dDp/dt (diameter change with time, nm/h)

• Depends on condensable gas concentrations

• GR const w/ Dp (small particles; kinetic regime)

• GR ~ Dp-1 (large particles; continuum regime)

• A moderately fast growth rate

• GR = 5 nm/h for kinetic (...lower for continuum)

• Expected growth due to condensation

• = (5 nm/h) x (1 week) = 800 nm (0.8 mm)

• Nucleation and ultrafine mode particles can

grow to fine mode

• Fine mode does not grow to coarse mode

Nuc Mode

(1-10 nm)

UF Mode

(10-100 nm)

Fine Mode

(0.1-1 mm)

Coarse Mode

(1-10 mm)

Cloud Drops

(10+ mm)

ation combustion

cond. cond.

• Note: condensation arrows show behavior of individual particle counts (aerosol number distribution)

• Looking at mass budgets of condensable gases

• Condensation ~ total particle surface

• ...mostly to fine mode (some UF and coarse)

Coagulation

• Basic expression for coagulation rate between

two particle size classes

jiijcoag NNKJ

Jcoag: coagulation rate (collisions cm-3 s-1)

Ni and Nj: number concentrations (cm-3) of particles in each size class

Kij: coagulation coefficient for size class i with size class j

• Note similarity to bimolecular reaction rate, r=k[A][B]

• Functional form of Kij depends on physical processes causing collision • Brownian motion (main thing for atmospheric aerosols)

• Particle diffusion is the most important process

Coagulation

• Brownian coagulation coefficient, Kij

• Kij maximum between very small (highly diffusive/mobile) and very large (large cross sections) particles

• → “coagulational scavenging” of ultrafines by accumulation mode (and coarse if present)

• Resulting particle lifetimes w.r.t coagulation

• Ultrafine particles: 1-10 hours

• Fine mode: few days

21212 DDDDK ppij

Dpi: particle diameters

Di : particle diffusivities

: non-continuum correction factor

particle size (target area) particle mobility

Nuc Mode

(1-10 nm)

UF Mode

(10-100 nm)

Fine Mode

(0.1-1 mm)

Coarse Mode

(1-10 mm)

Cloud Drops

(10+ mm)

ation combustion

cond. cond.

Dry Deposition: General Observations

• Ultrafine mode

• Diffusion gives higher vd than accumulation mode

• But coagulation tends to dominate losses under most

conditions

• Accumulation mode • Minimal deposition velocity

(timescale is ~months)

• Wet deposition matters more

• Coarse mode • Dry deposition is dominant

removal (timescale ~1 day)

Depositio

Particle Diameter

Acc. Ultra

-fine Coarse

Nuc Mode

(1-10 nm)

UF Mode

(10-100 nm)

Fine Mode

(0.1-1 mm)

Coarse Mode

(1-10 mm)

Cloud Drops

(10+ mm)

ation combustion

cond. cond.

Cloud Condensation Nuclei (CCN)

• In a particle-free atmosphere, a strong supersaturation

(~400% relative humidity) is required to nucleate new,

pure water droplets

• Instead, cloud water condenses onto pre-existing

particles: cloud condensation nuclei (CCN)

Clear Sky

(RH < 100%) Cloudy Sky

(RH > 100%)

(~100 nm)

particles

(aerosols) Cloud

droplets

(~10 mm)

Activation:

water condenses

on CCN to form

cloud droplets

Cloud Processing

• Only larger (100 nm or more) and more soluble

particles activate into cloud droplets

• From aerosol point of view, fate is

• cloud droplet precipitates → aerosol wet deposition

cloud droplet evaporates → «cloud processing»

• Cloud processing

• Aqueous chemistry • SO2 oxidation into sulfate

• formation of secondary organic aerosol (SOA) in aqueous?

• Other • Scavenging of «interstitial» (unactivated) aerosol particles

• Reduction in N concentration due to cloud collection proc.

Nuc Mode

(1-10 nm)

UF Mode

(10-100 nm)

Fine Mode

(0.1-1 mm)

Coarse Mode

(1-10 mm)

Cloud Drops

(10+ mm)

ation combustion

cond. cond.

activation

cloud proc.

• Nucleation mode (Dp < 10 nm) • Source: formation of new particles from super-saturated vapors

• Sinks: coagulate w/ larger particles or grow to Aitken mode by condensation (t ~ hours)

• Aitken mode (10 nm < Dp < 100 nm) • Sources: growth of nucleation mode, combustion emissions, (some) sea-

• Sinks: coagulate w/ larger particles, grow to accumulation model by condensation, removal by precipitation (wet deposition) (t ~ hours to days)

• Accumulation mode (100 nm < Dp < 1 mm) • Sources: growth of Aitken mode, combustion emissions, sea-spray, some

mineral dust

• Sinks: removal by wet deposition (major) and dry deposition (minor) (t ~ 4 to 8 days)

• Coarse mode (1 mm < Dp < 10 mm) • Sources: wind-blown sea-spray and mineral dust

• Sinks: dry deposition (major) and wet deposition (minor) (t ~ 1 to 3 days)

Aerosol Mass Budgets

(Tg/yr) (days) (Tg)

Aerosol Source Lifetime Burden

EC 7.7 8.1 0.2

Sulfate 120 5.7 1.9

Organics 190 4.7 2.5

Sea-salt 1800 0.8 3.9

Mineral Dust 2400 2.7 17.6

Burden = Source x Lifetime

• Coarse-mode particles

• large sources • Short-lived

(gravitational settling)

• Little or no anthropogenic contribution

(Tg/yr) (days) (Tg)

EC 7.7 8.1 0.2

Sulfate 120 5.7 1.9

Sea-salt 1800 0.8 3.9

• Fine-mode particles • Medium sources • Longer lifetimes • Large anthropogenic

contribution

(Tg/yr) (days) (Tg)

EC 7.7 8.1 0.2

Sulfate 120 5.7 1.9

Sea-salt 1800 0.8 3.9

• Small source • Long lifetime • Major source of

anthropogenic absorption

Sulfur Cycle

(dimethyl

sulfide)

SO2(g)

H2SO4(g)

(aerosol)

OH, NO3

radicals

OH radicals

condensation

onto existing

particles

nucleation of

new particles

SO2(aq)

dissolution

into cloud

SO42- (aq)

evaporation

of cloud drop

•DMS emitted by phytoplankton (10-20 Tg S/yr)

•SO2 emitted mostly by power plant combustion (70 Tg S/yr), volcanos (5 Tg S/yr)

•SO2 and sulfate undergo both dry/wet deposition

Organic Aerosol

emissions

Primary organic aerosol (POA) is

directly emitted in particle phase

Oxidation of VOCs

creates secondary

organic aerosol (SOA)

Volatile organic compounds

(VOCs) are gas-phase emissions

Aerosol Cycles

• Coarse, wind-blown particles

• Sea-salt and mineral dust

• Wind-blown emissions

• Large dry deposition, some wet deposition

• Elemental carbon

• No chemical production/loss

• Budget is simple: emissions = deposition

• «mixing state» (e.g. coated with other species?)

affects absorption efficiency

• effective as an ice nuclei?

Size and Composition

Nuc Mode

(1-10 nm)

UF Mode

(10-100 nm)

Fine Mode

(0.1-1 mm)

Coarse Mode

(1-10 mm)

Cloud Drops

(10+ mm)

condensable gases:

sulfate, nitrate,

secondary organic

aerosol

onto aerosol surface

combustion: EC

and primary

organic aerosol

wind-blown: NaCl and

crustal (Si, Ca, Fe)

Aerosol Number Budget (highly uncertain!)

Ultrafine Mode Fine Mode (CCN)

Emissions = 58

cm-3 day-1

100 nm

Growth = 12.2 cm-3

Deposition = 9

cm-3 day-1

Coagulation = 52

cm-3 day-1

Emissions = 3.2

cm-3 day-1

Deposition =

15.4 cm-3 day-1

GISS-GCM; global average; Sulfate, sea-salt, carbonaceous, dust

(Binary) Nucleation

J1 = 310 cm-3 day-1

J10 = 14 cm-3 day-1

Number

Outline

Aerosols Scattering Sunlight

Dust and smoke over Australia (Terra)

Aerosols Absorbing Sunlight

Kuwaiti oil fires

photo courtesy of Jay Apt (via Steve Schwartz)

Clouds and Climate

Atmosphere

•fluxes are W m-2

•Width of arrow proportional to flux

• 23% of incoming sunlight reflected by atmosphere (mostly by clouds)

• Without cloud reflection, the Earth would be ~15° C warmer

(absorbed)

(reflected)

photo courtesy of Amy Sage

Cloud Optics: Surface Area

In clouds, reflection and scattering are

proportional to surface area

Aerosol Cloud Reflectivity Effect

Polluted air mass

•Higher CCN concentration

•Lower Transmittance

•Higher reflectivity

•Less precipitation?

•Longer cloud lifetime?

Clean air mass

•Lower CCN concentration

•Higher Transmittance

•Lower reflectivity (albedo)

•Better chance of

precipitation?

•Shorter cloud lifetime?

photo courtesy of Amy Sage

Cloud Optics: Surface Area

For a given amount of liquid water (or ice):

• More pollution/CCN → More cloud droplets → More surface area

• → More scattering → Brighter cloud → Cooler Earth

Brighter polluted

(More CCN)

Darker clean

(Few CCN)

Aerosols and Clouds

AVHRR satellite “false color” image

Red: darker clouds (large droplets)

Green: brighter clouds (small

droplets)

Blue: clear sky

Power plant

Lead smelter

Oil refineries

Rosenfeld, Science (2000)

How direct is direct?

• Direct effect: scattering/absorbing sunlight

• Semi-direct effect:

• aerosol absorption heats atmospheric layer

• warmer air → lower relative humidity → less/no cloud

• Indirect effect: modifying cloud properties

• “brightness (first) effect”

• “lifetime (second) effect”

Forcing

Shortwave Longwave

Top-of-

atmosphere

Tropopause

Surface

Shortwave Longwave

Reference Atmosphere Perturbed Atmosphere

Forcing

• Change from reference to perturbed state • Anthropogenic forcing: e.g. pre-Industrial to now

• Future forcing: e.g. 2000 to 2100

• All-aerosol forcing: with vs without aerosols (includes natural

aerosol forcing, e.g. satellite)

• At an altitude • TOA or tropopause usually

• Surface forcing for hydrological cycle impacts

• Wavelength range • Except dust, aerosols generally have minimal impacts on IR

fluxes (so SW is usually whole story)

• Without feedbacks* • for GHGs, common to account for stratospheric adjustment

• *semi-direct and cloud lifetime require clouds to change

Forcing

• Ultimately, forcing is (or is not) a useful quantity to the extent

that it is a predictor of global temperature change

• Key parameter is l,“climate sensitivity”

• Implicit assumption is that sensitivity

• does not depend on the kind of forcing (GHGs, ozone, aerosols, etc)

• does depend on the particular climate model (stronger or weaker climate

feedbacks)

• Generally, aerosol forcings obey this assumption except

• black carbon absorption (triggers cloud changes, i.e. semi-direct effect)

• need to take care in defining/calculating cloud lifetime forcing

FT lglobal average

temperature

change

global average

radiative forcing

Climate “Forcing”

Radiative Forcing (W m-2)

Long-lived GHGs:

+2.6 W/m2 (+/- 10%)

Aerosol effects:

strong, but

uncertain cooling

Climate “Forcing”

Radiative Forcing (W m-2)

On the chart:

• Direct effect

• Cloud albedo (1st)

indirect

Not on chart:

• Semi-direct

(forcing or

feedback)

• Cloud lifetime

(2nd) indirect

Aerosol Forcing Constraints

• «Forward» calculations

• Emissions → aerosol conc → forcing

• Potential to give very strong cooling (i.e. more than

offsetting GHG forcing)

• «Reverse» calculations

• Observed T → what net forcing required?

• Net anthropogenic forcing on IPCC chart really

more constrained by reverse calculations than

forward calculations

Surface Dimming and Hydrological Cycle

• Reduces sunlight reaching surface

• Surface forcing can be greater than top-of-atmosphere (TOA)

• Slows evaporation of water from surface

• Drier climate, reduced hydrological cycle

Ramanathan et al. 2001

Aerosols: Other Effects

• Snow/Ice albedo modification

• Black carbon («soot») on snow and ice causes them

to darken

• May have high regional importance for melting

glaciers and ice pack

• Nutrient deposition to ocean

• Some oceanic ecosystems limited by various

micronutrients (e.g. Iron)

• Deposition of iron (dust, geoengineering) can

stimulate ocean biota, uptake of atmospheric C

• Ice nuclei

• Ice formation requires an aerosol surface (ice nuclei,

e.g. mineral dust) between 0 and -40 °C

Outline

• Global warming of 1.1 to 6.4°C by 2100 predicted

Climate Change Uncertainty

• “Climate sensitivity” is a key parameter

• Key parameter is l,“climate sensitivity”

• Blackbody Earth (no feedbacks): 0.2 to 0.3 °C per W/m2

• Climate models: 0.3 to 1 °C per W/m2 (1.5 - 4.5 °C for 2xCO2)

• Water vapor feedback and ice albedo feedback increase sensitivity

• In climate models, representation of cloud feedback is largest

source of uncertainty

• Uncertainty in aerosol forcing plays a key role in

• future projections

• interpretation of past

FT lglobal average

temperature

change

global average

radiative forcing

Strategies for Determining Climate Sensitivity

• Strategy 1: Climate Models (Theory) • Use a computer simulation to predict how much

temperature will change per amount of forcing

• Basic chemistry/physics of climate system are well known

• Problem is cloud feedback (parameterizations)

• Strategy 2: Earth in the past (Observations) • Example: Industrial Revolution (1800) to now

• We know greenhouse gas forcing very well

• We know temperature increase pretty accurately

• This tells us climate sensitivity

• Problem is concurrent changes in reflecting “haze” particles (aerosols)

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Forcing (W m-2

Aerosols and Climate Uncertainty

sensitivity

GHG forcing

20th century T

increase

Aerosol (haze)

+ GHG forcing

Two Uncertainties: Forcing / Sensitivity

Andreae et al. 2005

T = (high sensitivity) x (low forcing)

T = (low sensitivity) x (high forcing)

To be consistent with past warming, must be

within dotted lines

Climate Models: Sensitivity / Aerosols

Figure from Kiehl et al., GRL v34

doi:10.1029/2007GL0313832007

Climate Sensitivity and Aerosols

• Climate models “hindcast” the 20th century warming of ~0.6K • High sensitivity; low total forcing (strong aerosol

cooling)

• Low sensitivity; high total forcing (weak aerosol cooling)

• If we knew aerosol forcing better, we could use the 20th century temperature record to infer climate sensitivity

• Tuning / cheating by climate models?

• …or climate models as suite of possible realities

Uncertainty in Future Projections

Both high/low aerosol forcings

consistent with past 100 years

Andreae et al. 2005

Future diverges:

• GHGs accumulate

(long-lived)

• Aerosols don’t

(short-lived)

• Aerosol sources

being controlled

Air Quality vs Climate Mitigation

Brasseur and

Roeckner 2005

Constant

GHGs/aerosols

Anthro. sulfate

removed T = 0.8 K

(air quality

improvements

cause quick

warming, as

large as 20th

century)

Soot as Climate Mitigation?

• Black carbon

(“soot”) controls

have been

proposed for climate

mitigation

• Potentially cheap,

fast response

• (Somewhat)

quantified warming

effects: +0.3 to 1

• Offsetting cooling

effects less well

studied

Kuwaiti oil fires (photo

courtesy of Jay Apt)

Sunlight Absorption

Cloud Burnoff

Snow/Ice Darkening

Cloud Brightening: CCN

Co-emitted Reflecting

Particle Species: SO2,

POA, SOA

Warming Cooling

Outline

mixing

intra-

hemispheric

mixing

Challenges and Uncertainties

• Need to characterize particle • mass/number concentration

• size distribution: ~10 nm to 10 mm

• chemical composition: >hundreds compounds

• mixing state

• interactions with clouds

• Highly variable in space and time:

century decadal annual daily monthly hourly

Mean CO2

residence

mixed)

aerosol

residence

(not well

mixed)

Aerosol Variability

Old Challenge: Aerosol Monitoring

• Global SO4 models: same emissions, chemistry understood

• Global sulfate burdens differ by factor of 2

• Agree with surface (mostly N America and Europe) measured sulfate within ~20%

• Differences in remote areas and above PBL

• Errors in model burden will lead to similar errors in forcing

• Monitoring aerosol burdens essential to keep models ok

Barrie et al., 2001

Model-Measurement Integration

Models

Field Campaigns

Remote Sensing

In-situ Monitoring Networks

toxics.usgs.gov

MODIS (oceanmotion.org)

NASA ER-2 (cimss.ssec.wisc.edu)

Spatial coverage

Physical-chemical

properties

Temporal

coverage

Exploration,

synergy -vs-

Field Campaigns

• Chemical

weather

• Non-

representative

sampling(?)

• Long-term data

sets preferred for

model evaluation

• Better at

exploration

(process insights)

than monitoring

(burden, forcing)

NASA ER-2 (cimss.ssec.wisc.edu)

Outline

Particle Optics: Introduction

• Energy balance

• Incident = Transmission + Scattering + Absorption

• Define extinction

• Extinction = Scattering + Absorption

• Extinction is the loss of the direct beam

Incident light,

Transmission,

Scattering

Absorption

Particle Optics: Beer’s Law

• Beer’s Law

• dI(l) = -bext(l) I dx

• Extinction coefficient: bext (m-1)

• Depends on wavelength and air composition

Incident light,

Transmission,

Ix+dx(l)

Particle Optics

• Simple case: monodisperse aerosol (all

particles have same size)

• bext = Qext r2 N

• Qext (l,r) = extinction efficiency (no units)

• r = particle radius (m)

• N = particle number concentration (m-3)

• Qext: extinction efficiency

• relative to particle cross section

• Qext = 1 (every photon incident on particle undergoes

extinction)

Mie Theory: Regimes

• Mie theory gives Qext(l,r)

• Three regimes of behavior

• 1) Rayleigh: r << l (e.g. air molecules)

• Qext ~ r4 / l4

• 2) Mie: r ~ l (e.g. aerosols)

• Qext is complicated

• 3) Geometric: r >> l (e.g. cloud droplets)

• Qext ~ 2

Particle Optics

• Simple case: monodisperse aerosol (all

particles have same size)

• bext = Qext r2 N

• Geometric optics (e.g. clouds)

• Qext ≈ 2 (not a function of r)

• bext = 2 r2 N (proportional to total surface area!)

• Mie regime (e.g. aerosols)

• Qext ~ r; approx for fine mode (plus range of r)

• bext ~ r3 N (proportional to total mass!)

Outline

What Makes a CCN: Kohler Theory

• But Peqm above a particle depends on:

1. Temperature (Clausius-Clapeyron)

2. Dissolved solute (Raoult Effect)

• Decreases water vapor pressure

• Facilitates condensation / activation

3. Surface tension (Kelvin Effect)

• CCN / cloud droplets have significant surface free energy

• Destabilizes liquid water phase

• Increases water vapor pressure

• Inhibits condensation / activation

• Activation is a competition between (2) and (3):

lOHeqm P

Raoult Kelvin

100.0%

100.2%

100.4%

100.6%

0.1 1 10 100

Wet Diameter [mm]

What Makes a CCN? (Kohler Theory)

Kelvin effect – Surface Tension - Curvature

Overall Kohler theory: Combination

of Kelvin and solute effects

Solute effect – Raoult’s Law

Slide courtesy of Jeff Pierce

sea-salt particle (50 nm dry diameter)

Kohler Theory

0.1 mm dry diameter

Sc ~ 0.13%

0.07 mm dry diameter

Sc ~ 0.2%

0.04 mm dry diameter

Sc ~ 0.45%

Sea-salt (NaCl) particles: Number of CCN depends on:

1) Number of particles

2) Their sizes (size distribution)

3) Their composition (solubility)

Aerosol Activation

Diameter

• “Activation” = formation of cloud droplet

• involves a competition between solute

and surface tension effects

• A particle will activate if it has enough solute to overcome its surface tension

Depends on number

concentration above

“critical diameter”

Important factors: number, size, composition

Particles and Climate

“Direct Effect”

•Depends on aerosol mass

concentrations and

composition

•Easier to predict

•Well represented in IPCC

models doing long (century)

climate simulations

•“Traditional” models

“Indirect Effect”

•Depends on number

concentrations, size, and

composition

•Harder to predict: time-

consuming, poorly understood

processes

•Simulations typically 1-5 years

•“Microphysical” models

(developed over last 10 years)

Mixing State

• Mixing state: distribution of compounds across different particles

• Example: composition of 100 nm particles (somewhere) is 50% sulfate and 50% organics • «Internally mixed»: every 100 nm particle is half sulfate, half organic

• «Externally mixed»: half of the particles are pure sulfate; half are pure organic

• Reality is always somewhere between these ideal cases

• Internally/externally mixed refer to two particles of (approx) the same size • If a location has fine particles that are organic/sulfate and coarse particles that

are sea spray, this does not mean externally mixed

• Obviously, microphysical processes of condensation and coagulation govern conversion of externally mixed particles into internally mixed

• Observations show • External mixing near sources

• ...becomes more internally mixed over time

• Indirect effect: on global scale, internal mixing probably an ok assumption, more common than external mixing

• Direct effect: fairly insensitive to mixing state except

• For absorption efficiency of black carbon, aerosol mixing state matters (internally mixed absorbs more)

Conclusions?

• Aerosols are complicated

• ...but knowing key processes for each mode helps

• Large variety of climate impacts

• ...interactions with clouds tend to be most difficult

• Variety of physical properties

• number, size, composition, mass, mixing state, etc

• ...but usually only a subset is important for a given

problem

aerosols and the climate system - cnr · 2012-07-05 · aerosols and the climate system peter j....

Documents

whitecaps, sea-salt aerosols, ...

atmospheric and oceanic aerosols and ...

atmospheric aerosol properties and climate impacts ·...

modeling earth’s climate: water vapor, cloud, lapse rate...

pico project effects of aerosols on climate photo: l....

aerosols and climate

modeling the ef fects of atmospheric aerosols on climate ·...

toward a minimal representation of aerosols in climate...

anthropogenic sources of climate change. major anthropogenic...

possible impacts of pollution aerosols on …possible...

aerosols, climate, and the hydrological cycle ramanathan

atmospheric aerosols and climate

pollution, aerosols and climate change

aerosols: climate & air quality · aerosols: climate & air...

climate processes: clouds, aerosols and dynamics

7. aerosols and climate -...

impacts of aerosols on climate extremes in the usa

change in atmospheric mineral aerosols in response to...

pollution, aerosols and climate change - ucar center … ·...

direct climate forcing by anthropogenic sulfate aerosols:...