1

Saharan dust composition on the way to the Americas

and potential impacts on atmosphere and biosphere

K. Kandler

Institut für Angewandte Geowissenschaften, Technische Universität Darmstadt, 64287 Darmstadt, Germany

2

K. Kandler: Zum Einfluss des Saharastaubs auf das Klima – Erkenntnise aus dem

Saharan Mineral Dust Experiment (SAMUM)

The Saharan dust plume

over the Western

Atlantic Ocean

Karayampudi et al., 1999, doi: 10.1175/1520-0477(1999)080

3

K. Kandler: Zum Einfluss des Saharastaubs auf das Klima – Erkenntnise aus dem

Saharan Mineral Dust Experiment (SAMUM)

The Saharan dust plume

over the Western

Atlantic Ocean

Karayampudi et al., 1999, doi: 10.1175/1520-0477(1999)080

The Saharan dust plume

on its arrival over the Caribbean

Kallos et al. 2006, doi: 10.1029/2005JD006207

daily averaged surface dust concentration (in µg-3), modelled for 23 June 1993

PR

4

daily lidar scans starting Feb 19, 2008

Case study of a dust event

from Bodélé depression

reaching South America

from Ben-Ami et al. 2010

doi: 10.5194/acp-10-7533-2010

5

Dust composition and its dependencies,

interaction and potential impacts

geological basement

type of weathering

surface transport

chemical processing

emission meteorology

wet removal

heterogeneous

chemistry

dry removal

solar radiative impact

photochemistry

terrestrial

radiative impact wet processing

cloud impact

indirect radiative impact

marine ecosystem impact

terrestrial

ecosystem impact

human/plant/animal

health issues

sea-salt interaction

anthropogeneous/

biomass burning

aerosol admixture

EMISSION TRANSPORT DEPOSITION

6

Implications for radiation transfer

– dust radiative forcing

1data from Sokolik et al. 1999, doi: 10.1029/1998JD200048 2Otto et al. 2009, doi: 10.1111/j.1600-0889.2008.00389.x 3Evan et al. 2008, doi: 10.1029/2007GC001774

-30 -20 -10 0 10

90% Clay5% Quartz

5% Hematite

75% Clays20% Quartz

5% Hematite

80% Clays20% Hematite

Top-of the atmosphere (TOA) net

radiative forcing for different dust

mineralogical compositions(1)

ae

roso

l ra

dia

tive

eff

ects

, W

/m²

wa

rmin

g

co

olin

g

over ocean

ae

roso

l ra

dia

tive

eff

ects

, W

/m²

co

olin

g

Surface cooling

decrease in sea surface temperature

change in tropical cyclone activity(3)

Planetary surface(2) Top of the atmosphere(2)

over desert

Shortwave forcing case study, including

o measured aerosol size distribution

o measured vertical aerosol distribution

o measured planetary surface albedo

o measured particle shape

o derived particle refractive index

o derived particle single scattering albedo

cooling warming

7

Implications for radiation transfer –

dust composition and terrestrial radiation

1Hansell et al. 2011, doi:10.5194/acp-11-1527-2011 2data from Sokolik et al. 1998, doi: 10.1029/98JD00049

Mass extinction efficiency for different minerals

in the atmospheric window wavelength region(1)

0

10

20

30

40

TO

Afo

rcin

g,W

/m²

80

70

60

50

40

30

20

10

0

Su

rfac

ed

ow

nw

ell

ing

flu

x,

W/m

²

Sa

ha

ran

du

st

(Ba

rba

do

s)

Sa

ha

ran

du

st

(Nig

er)

Ne

ge

v d

us

t s

torm

Afg

ha

n d

us

t

SW

US

A d

us

t

Thermal infrared radiative forcing

for different dust compositions(2)

8

Dust composition and clouds

Modification by clouds

Uptake of gaseous precursor species via aqueous chemistry

Aqueous reaction with (acidic) species

Composition-selective removal by wet deposition

Internal mixing by droplet/particle scavenging or coalescence

Impact on clouds

Fresh dust particles can act as cloud condensation nuclei (dependency on mineralogy)(1)

Dust particles as giant cloud condensation nuclei (GCCN) may alter precipitation(2)

Increase of ice nucleus (IN) concentrations, IN at higher temperatures(3)

Mineral dust contributes by 21 to 84% to the IN concentration(4) over the Amazon basin

In a case study, more than 79 % of cloud droplets at Cape Verde contained dust particles(5)

Water vapor competition of GCCN versus smaller dust particles makes precipitation impact

depending on cloud conditions (i. e. liquid water content, but also gaseous chemistry)(6)

impact is ambiguous, depending on cloud microstructure(7)

Short-lived convective clouds are most sensitive(6)

Indirect impact through change of atmospheric dynamics by radiative impact

(surface cooling, increase in atmospheric stability)(6)

1Kumar et al. 2011, 10.5194/acp-11-3527-2011 2Yin et al. 2000, 10.1016/S0169-8095(99)00046-0 3Sassen et al. 2003, doi: 10.1029/2003GL017371 4Prenni et al. 2009, doi: 10.1038/NGEO517 5Twohy et al. 2009, doi: 10.1029/2008GL035846 6Rosenfeld et al. 2001, doi: 10.1073/pnas.101122798 7Seifert et al. 2011, doi: 10.5194/acpd-11-20203-2011

9

Dust and ecosystems

Marine ecosystems

Fe (and possibly, P) can limit bio-productivity on Oceans directly or by co-limiting N

fixation(1,2)

Saharan dust is made responsible for the degradation of coral reefs(3), but possible

pathways are still explored(4)

Toxic red tides in the Gulf of Mexico need dust Fe (and maybe P) input to start(5)

On the nature (and impact) of P on marine ecosystems “remarkably little is known“(2)

P input by dust can increase bacterial activity in Mediterranean freshwater ecosystems(6)

Terrestrial ecosystems

Forest ecosystems on extremely leached soils (like Amazonia) are short in nutrients (P, K)

which can be provided by dust fall(7,8)

For example, half of the total inputs to soil-and-biomass P can be derived from dust in

Puerto Rico’s Luquillo Mountains(9)

Forests on less leached soils can have deficit of Ca and K(10)

A tropical Andean forest in Ecuador receives considerable amounts of Ca and Mg from

Saharan dust(11)

1Jickells et al. 2005, doi: 10.1126/science.1105959 2Okin et al. 2011, doi: 10.1029/2010GB003858 3Shinn et al. 2000, doi: 10.1029/2000GL011599 4Rypien 2008, doi: 10.3354/meps07600 5Walsh et al. 2006, doi: 10.1029/2004JC002813 6Reche et al. 2009, doi: 10.4319/lo.2009.54.3.0869 7Swap et al. 1992, doi: 10.1034/j.1600-0889.1992.t01-1-00005.x 8Okin et al. 2004, doi: 10.1029/2003GB002145 9Pett-Ridge 2009, doi: 10.1007/s10533-009-9308-x 10Bond 2010, doi: 10.1007/s11104-010-0440-0 11Boy et al. 2008, doi: 10.1029/2007GB002960

10

Emission stage –

sources, composition, variation

geological basement

type of weathering

surface transport

chemical processing

emission meteorology

wet removal

heterogeneous

chemistry

dry removal

solar radiative impact

photochemistry

terrestrial

radiative impact wet processing

cloud impact

indirect radiative impact

marine ecosystem impact

terrestrial

ecosystem impact

human/plant/animal

health issues

sea-salt interaction

anthropogeneous/

biomass burning

aerosol admixture

EMISSION TRANSPORT DEPOSITION

11

Emission stage – general mineralogy

Dust composition is highly variably

Quartz and phyllosilicates are omnipresent

Phyllosilicates might be

(frequently reported) kaolinite, illite

(less frequently) chlorite, muscovite, montmorillionite, biotite, palygorskite, smectites and

inter-stratified clay minerals

Mostly, additional silicates are reported

(frequently) albite, anorthite, K-feldspars

(less frequently) chrysotile, orthoclase

Calcite, dolomite and sometimes apatite are found in varying abundance

Hematite, goethite and sometimes ilmenite are the main iron compounds

Sulfates, nitrates and chlorides are usually not reported with their mineralogical

denomination (some of them might [fractionally] recrystallize depending on

environmental conditions) In addition, a plethora of other mineral species are reported, including biological debris (diatomite), metal

oxides (rutile, periclase, baddeleyite, spinel), iron-rich minerals (lepidocrocite, limonite), carbonates

(aragonite, magnesite), sulfates (anhydrite, gypsum, thenardite, mirabilite, mascagnite, glauberite),

silicates (chloritoid, leucite, forsterite, zircon, enstatite) and graphite

12

0.23Mb

0.04-0.21Ad

0.61-0.84Av1

0.62Av22.08Av2

2.56CD

1.16Av1

0.40-0.65Or

0.40-0.46Kr

(SD)

5.17GF

(SD)

0.74-2.97To1

(SD)2.11BL

2.30-2.53Av1

0.80-0.83Wi

0.66-0.84Wi0.42MW

0.45Mo

0.83Ra

3.65Li

0.22He

0.86-1.39Sh

1.78-2.41Bu

0.88-2.12To2

4.29-8.40Ab

0.65Av2

0.25-2.17Br

0.45Ca

0.66Ca0.66Mo

0.71-1.19GT

0.62-0.85GT

0.37Mo

0.43Mo

3.35-7.24Mo

0.42Ca

3.56Ca

6.07Li

0.53Li

3.77Li

0.50Mou

0.63Mou

0.61Mou

0.74Mou

soil

dust(Ca+Mg)/Fe

0.25- 0.5

<0.25 >42 - 41 - 20.5- 1

1Scheuvens et al., in preparation for Earth. Sci. Reviews – details on original literature are given there 2Formenti et al. 2011, doi: 10.5194/acp-11-8231-2011

Composition of

Saharan dust and

topsoils characterized

by (Ca+Mg)/Fe ratio(1)

Emission stage – sources and composition

Major source

regions compiled

from different

techniques are

identified(2)

13

Mineralogical composition as function

of source regions – an example

data from Kandler et al. 2009, doi: 10.1111/j.1600-0889.2008.00385.x and Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x

DU1 DU3

Quartz

K-feldspar

Plagioclase

Calcite

Illite (1M)

Kaolinite

Smectites

Chlorite

Gypsum

Halite

Hematite

Rutile

Ja

n 1

4

Ja

n 1

5

Ja

n 1

6

Ja

n 1

7

Ja

n 1

8

Ja

n 1

9

Ja

n 2

0

Ja

n 2

1

Ja

n 2

2

Ja

n 2

3

Ja

n 2

4

Ja

n 2

5

Ja

n 2

6

Ja

n 2

7

Ja

n 2

8

Ja

n 2

9

Ja

n 3

0

Ja

n 3

1

Fe

b 0

1

Fe

b 0

2

Fe

b 0

3

Fe

b 0

4

Fe

b 0

5

Fe

b 0

6

Fe

b 0

7

Fe

b 0

8

Fe

b 0

9

DU2

dust phases by

meteorology and satellite obs.

Quartz

K-feldspar

Plagioclase

Calcite

Illite (1M)

Kaolinite

Smectites

Chlorite

Gypsum

Halite

Hematite

Rutile

Ma

i 1

3

Ma

i 1

4

Ma

i 1

5

Ma

i 1

6

Ma

i 1

7

Ma

i 1

8

Ma

i 2

0

Ma

i 2

1

Ma

i 2

3

Ma

i 2

4

Ma

i 3

0

Ju

n 0

1

Ju

n 0

2

Ju

n 0

3

Ju

n 0

4

Ju

n 0

5

Ju

n 0

6

Ma

i 3

1

Ma

i 2

5

Ma

i 1

9

Ma

i 2

2

Ma

i 2

6

Ma

i 2

7

Ma

i 2

8

Ma

i 2

9

dust intensity

dominant

major

minor

traces

detected

not det.

not invest.

I

K

14

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.00010.00030.0010.0030.010.03

0.5 to < 1 µm 1 to < 2.5 µm 2.5 to < 10 µm 10 to < 25 µm

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

(Na+

K+

Ca

)/S

i

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

(Mg

+F

e)/

Si

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Change in mineralogical composition with

particle size seen by chemical fingerprints

data from Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x

15

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.00010.00030.0010.0030.010.03

0.5 to < 1 µm 1 to < 2.5 µm 2.5 to < 10 µm 10 to < 25 µm

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

(Na+

K+

Ca

)/S

i

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

(Mg

+F

e)/

Si

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Change in mineralogical composition with

particle size seen by chemical fingerprints

F F

F F Q

Q Q

Q Q Q

Q Q

C C

C C

S S S

S S S

S

S

data from Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x

16

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.00010.00030.0010.0030.010.03

0.5 to < 1 µm 1 to < 2.5 µm 2.5 to < 10 µm 10 to < 25 µm

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

(Na+

K+

Ca

)/S

i

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Al/Si

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.1

0.2

0.3

0.4

0.5

0.6

(Mg

+F

e)/

Si

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Change in mineralogical composition with

particle size seen by chemical fingerprints

F F

F F Q

Q Q

Q Q Q

Q Q

C C

C C

S S S

S S S

S

S

data from Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x

SE on C-K

Ti

S

Si

Si

Fe

Mg

P

Q1

Q2

Q3

S

17

100 km

Bodélé depression – “a single spot”(1)?

Image from Chappell et al. 2008, doi: 10.1029/2007JD009032 1Koren et al. 2006, doi: 10.1088/1748-9326/1/1/014005

18

100 km

Bodélé depression – “a single spot”(1)?

Image from Chappell et al. 2008, doi: 10.1029/2007JD009032 1Koren et al. 2006, doi: 10.1088/1748-9326/1/1/014005

Data from Bristow et al. 2010, doi: 10.1029/2010GL043486

1 2 3 4

Fe/Ca ratio

2 km

19

Variability across the Ocean

– Fe/Ca as a tracer

Atomic ratio of Fe/Ca and its geometric standard deviation

1Kandler et al. 2009, doi: 10.1111/j.1600-0889.2008.00385.x 2Bristow et al. 2010, doi: 10.1029/2010GL043486 3Klaver et al. 2011, doi: 10.1002/qj.889 4DUST, Paris et al. 2010, 10.5194/acp-10-4273-2010 5Formenti et al. 2008, doi: 10.1029/2008JD009903 6Kandler et al. 2007, doi: 10.1016/j.atmosenv.2007.06.047 7Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x 8Formenti et al. 2003, doi: 10.1029/2002JD002648 9Reid et al. 2003, doi: 10.1029/2002JD002935 10Formenti et al. 2001, doi: 10.1029/2000JD900827

1.31

1.48 (2)

0.72

2.10 (1)

2.13

1.60 (7)

1.22

1.77 (6)

0.53

1.71 (9)

1.05 (8)

1.40

1.72 (3)

0.95

1.19 (4)

1.06 / 1.93 advected local

1.30 / 1.13 (5)

2.18 (10)

20

Variability across the Ocean

– Fe/Ca as a tracer

Atomic ratio of Fe/Ca and its geometric standard deviation

1Kandler et al. 2009, doi: 10.1111/j.1600-0889.2008.00385.x 2Bristow et al. 2010, doi: 10.1029/2010GL043486 3Klaver et al. 2011, doi: 10.1002/qj.889 4DUST, Paris et al. 2010, 10.5194/acp-10-4273-2010 5Formenti et al. 2008, doi: 10.1029/2008JD009903 6Kandler et al. 2007, doi: 10.1016/j.atmosenv.2007.06.047 7Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x 8Formenti et al. 2003, doi: 10.1029/2002JD002648 9Reid et al. 2003, doi: 10.1029/2002JD002935 10Formenti et al. 2001, doi: 10.1029/2000JD900827

1.31

1.48 (2)

0.72

2.10 (1)

2.13

1.60 (7)

1.22

1.77 (6)

0.53

1.71 (9)

1.05 (8)

1.40

1.72 (3)

0.95

1.19 (4)

1.06 / 1.93 advected local

1.30 / 1.13 (5)

2.18 (10)

0.6

0.81.0

2.0

4.0

ge

om

ean

+g

eo

std

dev

1 10 100

"PM"-x

Fe/Ca

0.2

0.4

0.6

0.81.0

2.0

geo

mea

n+

geo

std

dev

1 10 100

"PM"-x

Fe/Ca

0.4

0.6

0.81.0

2.0

ge

om

ean

+g

eo

std

dev

1 10 100

"PM"-x

Fe/Ca

21

Transport stage –

selective removal and admixture

geological basement

type of weathering

surface transport

chemical processing

emission meteorology

wet removal

heterogeneous

chemistry

dry removal

solar radiative impact

photochemistry

terrestrial

radiative impact wet processing

cloud impact

indirect radiative impact

marine ecosystem impact

terrestrial

ecosystem impact

human/plant/animal

health issues

sea-salt interaction

anthropogeneous/

biomass burning

aerosol admixture

EMISSION TRANSPORT DEPOSITION

22

Transport stage –

selective removal and admixture

By sedimentation

The largest particles > 50 µm are quickly removed

relative abundance of quartz and feldspars decreases, that of clay minerals increases

(carbonate contents are usually not strongly impacted)

Direct result: soil composition does not necessarily reflect generated dust composition, even

close to source

By admixing

For example, sulfate and soot particles may be added do dust aerosol (or vice versa) and

form an external mixture, which than can affect its radiative properties

By selective wet deposition

Dust particles containing larger amounts of soluble material may be preferentially removed

by rain-out / washout

Dust particles more sensitive to chemical processing (i. e. carbonates to nitric acid) may

quickly grow into large droplets under humid conditions and can be removed

23 Average

Chemical

composition

at different

locations

Morocco(1)

Tenerife(2) (SAL transport)

Cape Verde(3) (MBL transport)

0.0

0.2

0.4

0.6

0.8

1.0

rela

tive

ab

un

dan

ce

0.1 1 10 100

iron-rich

titanium-rich

carbonates

other calcium-rich

gypsum

sodium chloride

quartz

silicates

silicate sulfate mixtures

sulfates

carbonaceous

other

0.0

0.2

0.4

0.6

0.8

1.0

rela

tive

ab

un

da

nce

0.1 1 10 100

0.0

0.2

0.4

0.6

0.8

1.0

rela

tive

ab

un

dan

ce

oxides

carbonates

sodium chloride

quartz

silicates

silicate sulfate mixtures

sulfates

soot mixtures

other

1Kandler et al. 2009, doi: 10.1111/j.1600-0889.2008.00385.x 2Kandler et al. 2007, doi: 10.1016/j.atmosenv.2007.06.047 3Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x

depletion

admixture

mixing

(source-specific)

24

Transport stage – processing and mixing

geological basement

type of weathering

surface transport

chemical processing

emission meteorology

wet removal

heterogeneous

chemistry

dry removal

solar radiative impact

photochemistry

terrestrial

radiative impact wet processing

cloud impact

indirect radiative impact

marine ecosystem impact

terrestrial

ecosystem impact

human/plant/animal

health issues

sea-salt interaction

anthropogeneous/

biomass burning

aerosol admixture

EMISSION TRANSPORT DEPOSITION

25

Processes affecting dust composition

Uptake of non-dust species by mechanical mixing (sea-salt mixture not found at Cape Verde(1,2),

but reported in America(3); mixing seems most efficient for the transition size range 0.5 to 2 µm

particle diameter)

Condensation of secondary species (e. g., organics) on the dust surface(4)

Reaction of dust with (acidic) species, depending on dust composition (e. g., calcic vs. silicic)(5)

SO2 can be oxidized in dry state on dust surface in presence of ozone(6,7), but effect saturates(8,9)

Many pathways in aqueous state from SO2 to sulfate, efficiency depending on conditions (like

gaseous concentrations, cloud water pH, photochemistry...)(5,10)

Resulting changes in dust properties

Increase in sedimentation removal by increase in particle size(11)

Deposition of hygroscopic matter on dust particles increases CCN ability(12)

Sulfuric acid/sulfate and some organic matter decrease IN ability, but strength of effect depends

on mineralogy(13,14)

Changes in solubility of nutrients

Transport stage – processing

1Dall‘Osto et al. 2010, doi: 10.1016/j.atmosenv.2010.05.030 2Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x 3Worobiec et al. 2007, doi: 10.1016/j.atmosenv.2007.07.056 4Deboudt et al. 2010, doi: 10.1029/2010JD013921 5Cwiertny et al. 2008, doi: 10.1146/annurev.physchem.59.032607.093630 6Usher et al. 2002, doi: 10.1029/2002JD002051 7Ullerstam et al. 2002, 10.1039/b203529b 8Goodman et al 2001, doi: 10.1021/jp004423z 9Manktelow et al. 2010, doi: 10.5194/acp-10-365-2010 10Seinfeld & Pandis, Wiley 2006 11Zhang 2008, doi: 10.1111/j.1600-0889.2008.00358.x 12Gibson et al. 2007, doi: 10.1080/02786820701557222 13Cziczo et al. 2009, doi: 10.1088/1748-9326/4/4/044013 14Eastwood et al. 2009, doi: 10.1029/2008GL035997

26

0.0

0.2

0.4

0.6

0.8

1.0

nu

mb

er

fra

cti

on

inw

hic

h

co

mp

ou

nd

wa

sd

ete

cte

d

Dol

Cal

Sil(

Fe

Ti)

Sil

Qtz

Dol

Cal

Sil(

Fe

Ti)

Sil

Qtz

Dol

Cal

Sil(

Fe

Ti)

Sil

Qtz

Dependence of the chemical reactivity

on particle material over Niger

data from Matsuki et al. (2010), 10.5194/acp-10-1057-2010

sulfate nitrate chlorine

clear-sky

in-cloud

27

0.0

0.2

0.4

0.6

0.8

1.0

nu

mb

er

fra

cti

on

inw

hic

h

co

mp

ou

nd

wa

sd

ete

cte

d

Dol

Cal

Sil(

Fe

Ti)

Sil

Qtz

Dol

Cal

Sil(

Fe

Ti)

Sil

Qtz

Dol

Cal

Sil(

Fe

Ti)

Sil

Qtz

Dependence of the chemical reactivity

on particle material over Niger

data from Matsuki et al. (2010), 10.5194/acp-10-1057-2010

sulfate nitrate chlorine

clear-sky

in-cloud

large differences

in mixture

mixing by

reaction or in

aqueous phase,

not mechanically

reactivity least dependant on

particle material, maybe due

Ca sulfate being less

hygroscopic than Ca nitrate

and chloride, constraining

in-depth processing, and/or

due to dry sulfate formation

increase of mixing by

cloud processing

evident for hygroscopic

species, but also for

silicate particles

in general, also for clear-sky conditions reactivity

increases with relative humidity (not shown)

28

Mixing of dust with sulfate

at Praia, Cape Verde

Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x

Particles are

shown before and

after extensive

electron

bombardment

before after

silicate +

sulfate

silicate +

sulfate + ?

iron-rich grains

200 nm

loss of volatile

material

29

Mixing of dust and organics

observed in Senegal

Deboudt et al. 2010, doi: 10.1029/2010JD013921

SE image

particle and mesh support

Internal mixing of dust and carbonaceous matter is observed in a region with

coexisting dust and biomass burning aerosol

Relative abundance of internally mixed particles versus pure ones is highly variable

(5 to 50 % in this case study)

Carbonaceous matter is distributed homogeneously around the particle

most probably organic coating

Is coating reversible or not (high adsorption efficiency of clays for organics)?

Si map

particle only

C map

particle (and support) visible

30

Transport/Deposition stage – particular

importance of iron and phosphorus

geological basement

type of weathering

surface transport

chemical processing

emission meteorology

wet removal

heterogeneous

chemistry

dry removal

solar radiative impact

photochemistry

terrestrial

radiative impact wet processing

cloud impact

indirect radiative impact

marine ecosystem impact

terrestrial

ecosystem impact

human/plant/animal

health issues

sea-salt interaction

anthropogeneous/

biomass burning

aerosol admixture

EMISSION TRANSPORT DEPOSITION

31

Iron and phosphorus as nutrients

As of today, Fe and P seem to be the most important nutrients, but knowledge about dust

Ca, Mg, K supply is sparse

For soluble Fe fraction (i. e. bio-availability), a range between 0.01 and 80 % is reported(1,2)

Fe solubility depends on source composition, atmospheric processing, already existing Fe

concentrations, dust concentration, biological influences(2,3)

Fe solubility increases with decreasing pH especially for low pH values(4)

Fe solubility was found to increase with atmospheric processing intensity(5)

Most soluble Fe comes from clay minerals, not from Fe oxides(6)

Fe-rich nanoparticles can form after acidic solution of soil(7), which may be directly or at

least at higher rates bio-available(2)

High aerosol Fe content in general does not mean similarly high bio-available Fe(5,6)

Total P content in Saharan dust between 0.04 and 1.7% (mostly below 1%)(8,9,10)

Acidification of aerosol (e. g. anthropogenic gas emissions) makes P more bio-available(11)

High relative humidity may be counterproductive in increasing P-availability due to more

neutral pH(11)

P is assumed to be present as apatite, but also other phases are very probable

1Mahowald et al. 2005, doi: 10.1029/2004GB002402 2Baker et al. 2010, doi: 10.1016/j.marchem.2008.09.003 3Shi et al. 2011, doi: 10.1029/2010GB003837 4Cwiertny et al 2008, doi: 10.1029/2007JD009332 5Chen et al. 2004, doi: 10.1029/2003JD003958 6Journet et al. 2008, doi: 10.1029/2007GL031589 7Shi et al. 2009, doi: 10.1021/es901294g 8Guerzoni et al. 2005, doi: 10.1007/b107149 9Guieu et al. 2002, doi: 10.1029/2001JD000582 10Singer et al. 2003, doi: 10.1006/jare.2002.1023 11Nenes et al 2011, doi: 10.5194/acp-11-6265-2011

32

Phosphorus in Saharan dust

P

in part from Scheuvens et al. 2011, doi: 10.1111/j.1600-0889.2011.00554.x

Position of P on

single dust particles

P 0°

90° mirr.

33

Deposition stage –

variability and future needs

geological basement

type of weathering

surface transport

chemical processing

emission meteorology

wet removal

heterogeneous

chemistry

dry removal

solar radiative impact

photochemistry

terrestrial

radiative impact wet processing

cloud impact

indirect radiative impact

marine ecosystem impact

terrestrial

ecosystem impact

human/plant/animal

health issues

sea-salt interaction

anthropogeneous/

biomass burning

aerosol admixture

EMISSION TRANSPORT DEPOSITION

34

Deposition stage – phenomenology and

dust composition

Type of deposition

In Florida, most dust is deposited by wet deposition(1)

At Bermuda, most dust is deposited by dry deposition(2)

Mixing with sea-salt could increase particle size and promote (dry) deposition(2,3,4,5)

Variability

High temporal variation in mass: 30 to 90% of annual dust deposition occurs on 5% of the

days, particularly at the edge of the Saharan dust plume(6,7)

Low temporal variation in composition: two years of measurement at Florida and

Barbados(8) and low spatial variation in composition over Florida(1)

Temporal variability (Fe/Ca) at Puerto Rico still in the same range as over the Ocean(9,10)

General

Dust arrives internally mixed with different species in America(5,11)

Information on speciation of major nutrients and their availability is sparse(12)

1Prospero et al 2010, doi: 10.1029/2009JD012773 2Tian et al. 2008, doi: 10.1029/2007GC001868 3Zhang et al. 2006, doi: 10.1016/j.atmosenv.2005.10.037 4Deboudt et al. 2010, doi: 10.1029/2010JD013921 5Worobiec et al. 2007, doi: 10.1016/j.atmosenv.2007.07.056 6Mahowald et al. 2009, doi: 10.1146/annurev.marine.010908.163727 7Bonnet et al. 2006, doi: 10.1029/2005JC003213 8Trapp et al. 2008, doi: 10.1016/j.marchem.2008.10.004 9Reid et al. 2003, doi: 10.1029/2002JD002935 10Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x 11Krejci et al. 2005, doi: 10.5194/acp-5-3331-2005 12Okin et al. 2011, doi: 10.1029/2010GB003858

35

Composition of aerosol deposited

in the northern Amazonian basin

Worobiec et al. 2007, doi: 10.1016/j.atmosenv.2007.07.056

soil dust refers to non-local (Saharan) dust,

determined by trajectory analysis

Aged sea salt + organic

Sea salt + organic

Soil dust + organic

Aged sea salt

+ soil dust

Biogenic

Organic

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

25 Mar1998

26 Mar 27 Mar 29 Mar 30 Mar 1 Apr 2 Apr 6 Apr 7 Apr 8 Apr 10 Apr 11 Apr 12 Apr

particle diameter 0.5 to 2 µm

36

What is missing?

General effects

Emission: We have seen considerable amounts of sulfate already on dust in Africa – what is the

degree of processing at the soil surface, and how much is it processed during transport?

Emission/Transport: Regarding the Fe solubility and bio-availability, we need to know more on

their dependence on source mineralogy, on in-soil and in-air processing (which gaseous or

particular species yield what effect?), and how these impact on ecosystems with shorter or longer

retention time

Emission/Transport: Similar questions arise for phosphorus availability, but the level of knowledge

is even lower than for iron

Transport: For cloud impact and also the dust processing, we need to know more about the

particle mixing state – preferrably spatially (3D) and particle-size-resolved

Transport/Deposition: We know that dust has an non-linear impact on cloud droplet and ice

nucleation and, thus, precipitation, but which are the dominating effects? – Possibly by a

combination of an intensive field campaign and subsequent quantification (monitoring)

Transport/Deposition: Besides Fe and P, also Ca, Mg and K from African dust are termed as

potential nutrient for terrestrial ecosystems – what is their impact in relation to other sources? How

changes their bioavailability by processing dependent of different atmospheric acids?

Transport/Deposition: We know that organic coatings exist on dust – do they derive from biomass

burning (only), from marine processes, can they be acquired just before deposition? What do they

do to cloud impact (CCN, IN properties), and can organic acids promote bioavailability in time?

Deposition: Does internal mixing increase deposition flux? Does particle shape have an impact?

37

What is missing? (continued)

Spatial and temporal variation

Dust sources have small-scale compositional variation and are not time-invariant

Is it feasible to create a adequately-resolved “cadaster”? What can we generalize?

What is the influence of this variation on the receptors (clouds, ecosystems)?

Several intensive field experiments with different foci yielded information on dust

composition, but the longest ones lasted one season

How should they be rated, given a considerable variability on inter-seasonal scale

(NAO) and the strong event-like occurrence of large dust loads?

Many measurements show high daily variation, measures for variability change as single

days are excluded measurements on too short time scales to capture variability

Need of long-term monitoring (in terms of composition, single particle measurements

would be useful)

With respect to complexity of dust interactions

“Supersite” monitoring – which locations can be set-up upgraded?

We know that dust plumes can be sharp-edged on inhomogeneous (particularly on vertical

axis, but also on horizontal one), but we can only monitor at single spots continuously

Need of network-like observations (aircraft- and ship-based monitoring, e. g. CARIBIC

package)