Aerosols in Amazonia: Urban impacts on a pristine atmosphere at the GoAmazon 2014/15 Experiment

Climate

Ecosystems

Atmospheric

Composition

Paulo Artaxo, Scot Martin, Allen Goldstein, Jose L. Jimenez, Suzane de Sá, Pedro

Campuzano-Jost, Samara Carbone, Joel Brito, Brett Palm, Douglas Day, Gabriel Isaacman-VanWertz, Lindsay Yee, John

Shilling, Johanes Schneider, Roger Seco, Ryan Thalman, Liz Alexander,

Jian Wang, H. Barbosa, B. Holanda, G. Cirino, L. Rizzo, R. Souza, Andi Andreae, C.

Pohlker, M. Kruger, J. Saturno and many others

University of São Paulo, BrazilAMS Users Meeting

GoAmazon2014/15 ExperimentThe central idea...

Manaus is a city of 2 million people surrounded by just forest in a radius of 1.500 Km. UNIQUE situation.

The aim of the GoAmazon 2014/15 experiment is to analyze how the emissions of pollutants of the city of Manaus interacts with the Amazonian natural biogenic emissions from the forest and how are the impacts on the climate over the forest and ecosystem functioning.

Manaus

Aerosol Particle Number Conc’n (CN)

Aerosol Particle Cloud Condensation Nuclei (CCN) Activity

Cloud Droplet Number Concentration (CDNC)

Lightning Strikes

Natural

Processes of

Rainforest

Ecosystem

Anthropogenic

Emissions

How particles are formed from the interactions of forest biogenic VOCs with urban emissions?

500 km

Manacapuru

ATTO

Manaus

Seven measuring sampling sites in Central Amazonia

TWO years: Jan 2014-Dec 2015

ATTO

Manaus

Manacapuru (T3)

Instrumentation deployed at GoAmazon 2014/15

Aerosols

• Surface: CCN, CLAP, CPC, PSAP, Neph

• Size distribution, optical properties,

Chemistry (AMS), phase, etc...

• Column: Sunphotometer

Atmospheric Profiling

• Microwave Radiometers (MWR):

Profiler, high frequency, 3-channel

• Balloon-borne Sounding System

(SONDE)

Clouds

• Lidar: Micropulse, Raman and Doppler

• Cloud Radars: Radar Wind Profiler, W-

band, Scanning W-Band and Ka-Band

• Narrow Field of View

• Total Sky Imager, Ceilometer

Radiometers

• Atmospheric Emitted Radiance

Interferometer, Infrared Thermometer,

Multifilter Rotating Shadowband

Radiometer, Upwelling Radiation,

Multifilter Radiometer, Downwelling

Radiation, Solar Array Spectrometer-

Hemispheric, Solar Array Spectrometer-

Zenith

Surface Meteorology

• Eddy Correlation Flux Measurement

System, Surface Energy Balance System,

Meteorological Instrumentation, Optical

Rain Gauge, Tower Camera

“Intensive Airborne Research in Amazonia

2014” (IARA-2014)

G5 HALO plane - “High Altitude and Long Range Research Aircraft” at the “ACRIDICON: Aerosol, Cloud, Precipitation, andRadiation Interactions andDynamics of CONvective Cloud Systems”.

G-1 Flight Paths during GoAmazon

Phase 1 (Wet season) Phase 2 (dry season)

16 flights – 42.8 hours

Feb 15th - March 26st , 2014

19 flights – 53.7 hours

Sep 1st - Oct 10th , 2014

ACRIDICON Flights G5-HALO plane dry season 2014

Large scale back trajectories to T0a-ATTO

Note the change from wet to dry season

For the wet season AMAZE 2008

Martin et al., 2009, Andreae et al., 2015

11

organicssulfatenitrateammoniumchorideBCewater

ATTO: 1.5 years of measurements - Organics dominate PM1 → 6 times larger in the dry season

WaterTOTAL = waterorganic + waterinorganic

ISORROPIA2Kappa x organics

ATTO Aerosol Size distribution

Wet season Dry season

13

Dry + Wet season Wet season

ATTO: Good agreement for the mass closure

The addition of water into the mass closure is likely inside the

uncertainty of the intercomparison between the instruments.

14

ATTO: Different air masses bring African smoke and marine aerosols

Events last from 2 to 10 days;

Tight agreement between sulfate and BCe;

Events can be associated with chloride or not;

Backward wind trajectories;

Identified during all months from Jan-Jul.

African smoke

15

ATTO: Secondary organic aerosol comprises ~80% of OA in the dry season

LV-OOA – oxygenated organic aerosol 40%

IEPOX- SOA - Isoprene Epoxydiols-derived secondary organic 20%

BBOA – Biomass burning organic aerosol 18%

SV-OOA – semi-volitile oxygenated organic aerosol 22%with biomass burning markers

LV-OOA

SV-OOA withBB markers

IEPOX-SOA

BBOA

Samara Carbone results

Mas

sco

ncent

rati

on(µ

g m

-3)

Inorg-N

Org-N

ATTO: Org-Nitrate comprises 2/3 of the nitrate signal

Analysis PMF and NO+/NO2+ ratio organic nitrates ~5-10

inorganic nitrates ~2.5Xu et al., 2015 (ACP)

T0a Sulfate is related to BC, but with various ratios

T0a - ATTO

Different sources, modulated by different Long range transport processes

BC from Africa wet season

The organics made up to 76% of the fine particles and when investigated as a function of the scattering coefficient (σ450) different patterns (with different slopes) were observed over time. BC also shows different patterns but less pronounced

T0a ATTO - Organics versus light scattering and absorption

What drives light scattering and absorption for PM1?

T0z – ZF2 Dry season ACSM

T0z – ZF2 – Diurnal profiles of PMF FactorsT0z – ZF2 – PMF factors versus parameters

Organics dominates scattering,not sulfates

Results from T2 (Manaus) and T3 (70 km downwind)

Wet Season

Black Carbon

Rush hour – Manaus

Benzene and CO

Benzene – Wet Season CO – Wet Season

T2 (Tiwa) OA PMF analysis Dry season

HOA

BBOA

Fac 91

LO-OOA

IEPOX OA

MO-OOA

Primary urban

Primary biomass burning

Brick kiln ? / Aged BBOA?

Fresh SOA

Isoprene SOA

Processed SOA

T2 - OA PMF analysis

HOA BBOA

Particle composition at T3

Suzane S. de Sá

Comparison of statistics between seasons at T3

Lower and upper whiskers represent 5 and 95 percentiles, respectively. Star shows the mean.

• Total mass concentrations are a factor of 8 higher in IOP2, yet relative mass contributions are similar (shown in previous figure).

Suzane S. de Sá

Comparison of diel trends between seasons at T3

• Sulfate shows a similar relative diel trend between seasons. This suggests that the production and loss processes of sulfate are not as affected by shifts from wet to dry season in the same way that the other species are, which is consistent with the idea that the main source of sulfate is the Manaus plume.

• The other species have flatter diel trend in the dry season, which suggestsa shift from dominance of photochemistry production in the wet season to dominance of regional aerosol advection (large biomass burning events) in the dry season.

Suzane S. de Sá

Comparison of (fresh) biomass burning influence between seasons at T3

• A remarkable difference is observed between seasons regarding the range of measured f60 values.

• f60 will likely be a valuable marker for ongoing analysis of influence from different plumes during IOP2.

Suzane S. de Sá

PMF of organic spectra for T3

IEPOX-SOA in Amazonia

79%

1%3%4%

13%

85%

1%3%

11%

IOP1(Wet season)

IOP2(Dry season)

OrganicSulfateAmmoniumNitrateChloride

PMF

PMF

Other factors83%

IEPOX-SOA17%

Other factors85%

IEPOX-SOA15%

Suzane S. de Sá

Insights into composition of the IEPOX-SOA factor

IEPOX-SOA in Amazonia

Isoprene photooxidation, HO2-dominant pathway

R2 = 0.88

R2 = 0.57

Oligomers…

[Adapted from Surrat et al., 2010]

• Temporal correlations with SV-TAG tracers provide insights into IEPOX-SOA composition and corroborates validity of PMF results.

Suzane S. de Sá

SV-TAG preliminary results from Allen Goldstein group

Organic aerosols from ATTO to Tiwa and Manacapuru (with BC)

T0a

T2

T3

Wet Dry

Radar Profiles of Frequency of Cloud Occurrences

David Troyan, Mike Jensen, Tami Toto, Scott Giangrande and Karen Johnson

Dry season 12 Km

Wet Season: Low Clouds

Rachel Albrecht, USP.

Lightning strike frequencies over T0a (clean), T1 (urban), and T3 (downwindurban). Substantial differences over these sites are apparent year around, indicatingthe connection between urban emissions, clouds, and lightning.

Wet Season Dry Season

Lightning strike frequency increases in the pollution plume

compared to the natural conditions outside of the plume

a. IOP1

Aerial View of T3G-1 Flight Paths during GoAmazon

10 100 5000

200

400

600

800

1000

1200

dN

/dlo

g1

0D

p (

cm

-3)

Dp (nm)

0 500 10000

1000

2000

3000

4000

5000

6000

N (Dp>10nm)

(STP, cm-3)

Altitu

de

(m

)

0 10 200

1000

2000

3000

4000

5000

6000

sp

(STP, Mm-1)

Altitu

de

(m

)

598 m

1798 m

3020 m

4244 m

5459 m

Vertical profile of particle size distribution under pristine condition during wet season

March 7, 2014

Entrained FT aerosol a source

of particle number in BL? (Jian Wang, BNL)

Impact of Manaus plume on aerosol properties

2 1345

March 13th, 2014

14.4 14.6 14.8 15 15.2 15.4

5000

10000

15000

N

(Dp>

10

nm

) (c

m-3

)

14.4 14.6 14.8 15 15.2 15.4

80

100

120

140

CO

(p

pb

)

14.4 14.6 14.8 15 15.2 15.4

500

1000

1500

CC

N N

(c

m-3

)

N

CCN 0.22%

NCCN

0.46%

14.4 14.6 14.8 15 15.2 15.40

5

10

15

sp @

55

0 n

m (

Mm

-1)

14.4 14.6 14.8 15 15.2 15.4 10

100

400

Dp (

nm

)

UTC (hours)

dN

/dlo

g1

0D

p,

(cm

-3)

10

100

1000

10000

21 3

45

Evolution of aerosol size distribution in Manaus plume (March 13, 2014, Wet season)

10 100 5000

1

2

3

4

5

6x 10

4

dN

/dlo

g1

0D

p (

cm

-3)

Dp (nm)

3

4

2

Background

5

10 100 50010

1

102

103

104

105

dN

/dlo

g1

0D

p (

cm

-3)

Dp (nm)

3

4

2

Background

5

Growth of particles inside Manaus plume due

to condensation of secondary species.

Slide prepared by Scot Martin

CPC COUNTS, GoAmazon2014/5, IOP1, 16 March 2014, 14:41 to 15:49 UTCIARA: Karla Longo, Beat Schmid, Scot Martin, and many important collaborators

CPC COUNTS, GoAmazon2014/5, IOP1, 17 March 2014, 16:24 to 17:31 UTC

Slide prepared by Scot Martin

PARTICLE ORGANIC, GoAmazon2014/5, IOP1, 17 March 2014, 16:24 to 17:31 UTC

Slide prepared by Scot Martin

PARTICLE ORGANICGOES UP

PARTICLE SULFATE, GoAmazon2014/5, IOP1, 17 March 2014, 16:24 to 17:31 UTC

Slide prepared by Scot Martin

PARTICLE SULFATEGOES UP

Organic, Nitrate, and Sulfate Mass Concentrations

Data Source: John Shilling, DOE AAF G1 Platform

500 m, 11 AM local, 13 March 2014

Organic aerosol, nitrate and sulfate all growing up from clean to Polluted conditions

NITRIC OXIDE, GoAmazon2014/5, IOP1, 17 March 2014, 16:24 to 17:31 UTC

Slide prepared by Scot Martin

ISOPRENE, GoAmazon2014/5, IOP1, 17 March 2014, 16:24 to 17:31 UTC

Slide prepared by Scot Martin

Slide prepared by Scot Martin

ISOPRENE CONCENTRATIONS, GoAmazon2014/5, IOP1, 16 March 2014IARA: Karla Longo, Beat Schmid, Scot Martin, and many important collaborators

Thanks for the attention!!

GoAmazon is providing a fantastic data set to study key atmospheric process in tropical regions…