observations and modeling of the green ocean amazon

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Observations and Modeling of the Green Ocean Amazon Climate Ecosystems Atmospheric Composition Presented by Scot Martin (PI), Harvard University, in contribution to SAMBBA Meeting (April 2012)

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Observations and Modeling of the Green Ocean Amazon. GoAmazon2014. Green Ocean Amazon 2014. Carbon CycleCloud Life Cycle Aerosol Life Cycle. Presented by Scot Martin (PI), Harvard University, i n contribution to SAMBBA Meeting (April 2012 ). Climate Ecosystems - PowerPoint PPT Presentation

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Page 1: Observations  and Modeling of the Green Ocean  Amazon

Observations and Modeling of the Green Ocean Amazon

ClimateEcosystems

Atmospheric Composition

Presented by Scot Martin (PI),Harvard University,

in contribution toSAMBBA Meeting

(April 2012)

Page 2: Observations  and Modeling of the Green Ocean  Amazon

Outline of Presentation

• WHY this experiment, part 1?• WHERE will this experiment take place?• WHEN will this experiment take place?• WHAT instrumentation and facilities are part of

experiment?• HOW is the experiment organized?• WHY this experiment, part 2?

Page 3: Observations  and Modeling of the Green Ocean  Amazon

Outline of Presentation

• WHY this experiment, part 1?• WHERE will this experiment take place?• WHEN will this experiment take place?• WHAT instrumentation and facilities are part of

experiment?• HOW is the experiment organized?• WHY this experiment, part 2?

Page 4: Observations  and Modeling of the Green Ocean  Amazon

Source: Pöschl, Martin, et al., "Rainforest aerosols as biogenic nuclei of clouds and precipitation in the Amazon," Science, 2010, 329, 1513-1516.

Cloud Life Cycle, Aerosol Life Cycle, Aerosol-Cloud-Precipitation Interactions, Carbon Cycle are all represented in this schematic.

GoAmazon2014: What is the effect of pollution on… these cycles and the coupling among them?

Cloud Life Cycle, Aerosol Life Cycle, Aerosol-Cloud-Precipitation Interactions, Carbon Cycle are all represented in this schematic.

GoAmazon2014: What is the effect of pollution on… these cycles and the coupling among them?

Page 5: Observations  and Modeling of the Green Ocean  Amazon

Reference: Pöschl, Martin, et al., “Rainforest aerosols as biogenic nuclei of clouds and precipitation in the Amazon,” Science, 2010, 329, 1513-1516.

Particle-Limited Regime

Anthropogenically affected continents;Year 2012

AmazonBasin;Year1750

Example: Sensitivity of Cloud Droplet Number Concentration (CDNC) to Pollution (aka “Aerosol Indirect Effects”)

Amazon Basin:

Low aerosol number concentrations +

High water vapor concentration =

Especially susceptible.

Possibility of dramatic changes in energy flows and rainfall patterns

Page 6: Observations  and Modeling of the Green Ocean  Amazon

Outline of Presentation

• WHY this experiment, part 1?• WHERE will this experiment take place?• WHEN will this experiment take place?• WHAT instrumentation and facilities are part of

experiment?• HOW is the experiment organized?• WHY this experiment, part 2?

Page 7: Observations  and Modeling of the Green Ocean  Amazon

Downwind of Manaus

•111 by 60.8 km represented by this box.•Wind speeds at 1 km altitude are typically 10 to 30 kph.•T2→T3 transit time of 2 to 6 hr.

Page 8: Observations  and Modeling of the Green Ocean  Amazon

Reference: Kuhn, U.; Ganzeveld, L.; Thielmann, A.; Dindorf, T.; Welling, M.; Sciare, J.; Roberts, G.; Meixner, F. X.; Kesselmeier, J.; Lelieveld, J.; Ciccioli, P.; Kolle, O.; Lloyd, J.; Trentmann, J.; Artaxo, P.; Andreae, M. O., “Impact of Manaus City on the Amazon Green Ocean atmosphere: Ozone production, precursor sensitivity, and aerosol load,” Atmos. Chem. Phys. 2010, 10, 9251-9282.

Page 9: Observations  and Modeling of the Green Ocean  Amazon

Reference: Kuhn, U.; Ganzeveld, L.; Thielmann, A.; Dindorf, T.; Welling, M.; Sciare, J.; Roberts, G.; Meixner, F. X.; Kesselmeier, J.; Lelieveld, J.; Ciccioli, P.; Kolle, O.; Lloyd, J.; Trentmann, J.; Artaxo, P.; Andreae, M. O., “Impact of Manaus City on the Amazon Green Ocean atmosphere: Ozone production, precursor sensitivity, and aerosol load,” Atmos. Chem. Phys. 2010, 10, 9251-9282.

Page 10: Observations  and Modeling of the Green Ocean  Amazon

Downwind of Manaus

The deployment site is situated in the steady trade winds such that it experiences the extremes of:

(i) a pristine atmosphere when the Manaus pollution plume meanders; and

(ii) heavy pollution and the interactions of that pollution with the natural environment when the plume regularly intersects the site.

Reminder: GoAmazon2014 Theme: What is the effect of pollution on… these cycles and the coupling among them?

Page 11: Observations  and Modeling of the Green Ocean  Amazon

December 2011: Fence and Weather Station

Page 12: Observations  and Modeling of the Green Ocean  Amazon

Outline of Presentation

• WHY this experiment, part 1?• WHERE will this experiment take place?• WHEN will this experiment take place?• WHAT instrumentation and facilities are part of

experiment?• HOW is the experiment organized?• WHY this experiment, part 2?

Page 13: Observations  and Modeling of the Green Ocean  Amazon

Dates of GoAmazon2014

AMF Operations (T3 ground site)• 1 January until 31 December 2014

AAF Operations (aircraft)• 15 February until 26 March 2014 (wet

season) (75 hrs)• 1 September until 10 October 2014 (dry

season) (75 hrs)

Aircraft operations correspond to the two intensive operating periods planned for the experiment.

Page 14: Observations  and Modeling of the Green Ocean  Amazon

Outline of Presentation

• WHY this experiment, part 1?• WHERE will this experiment take place?• WHEN will this experiment take place?• WHAT instrumentation and facilities are part of

experiment?• HOW is the experiment organized?• WHY this experiment, part 2?

Page 15: Observations  and Modeling of the Green Ocean  Amazon

ARM Mobile Facility in Amazônia (AMFA)

Page 16: Observations  and Modeling of the Green Ocean  Amazon

Precision Spectral Pyranometer (PSP) x 2 Precision Infrared Radiometer (PIR) x 2 Shaded Black & White Pyranometer (B/W) Shaded Precision Infrared Pyrgeometer (PIR) Normal Incidence Pyrhiliometer (NIP) Infrared Thermometer (IRT) x 2 Multi-Filter Rotating Shadowband Radiometer

(MFRSR) Narrow Field of View Zenith Radiometer (NFOV) Optical Rain Gauge (ORG) Anemometers (WND) Temperature/Relative Humidity Sensor (T/RH) Barometer (BAR) Present Weather Detector (PWD) Eddy Correlation Flux Measurement System (ECOR) Shortwave Array Spectrometer (SAS-He, SAS-Ze)

Microwave Radiometer (MWR) Microwave Radiometer Profiler (MWRP) Microwave Radiometer 90/150 (MWR-HF) Doppler Lidar (DL) Ceilometer (CEIL) Balloon Borne Sounding System (BBSS) W-band ARM Cloud Radar - 95GHz (WACR) Ka-W Scanning ARM Cloud Radar (SACR) Atmospheric Emitted Radiance Interferometer (AERI) Total Sky Imager (TSI) Aerosol Observation System (AOS)

CCNCPSAPNephelometers X 2

Radar Wind Profiler – 1290MHz (RWP) Cimel Sunphotometer (CSPHOT)

AMF1 – 7 x 20’ sea containers1 full-time on-site technician

AMF1

LANL Solar Fourier Transform Spectrophotometer (FTS) (Dubey) (OCO-2 validation)

Page 17: Observations  and Modeling of the Green Ocean  Amazon

Mobile Aerosol Observing System (MAOS) – 2 x 20’ sea containers (MAOS-A & MAOS-C)

2 x full time post-docs (supplied by ARM) Guest operational personnel (approx. 5)

SOnic Detection And Ranging (SODAR) System (1000 to 4000 Hz) Ultra-High Sensitivity Aerosol Spectrometer (enhanced) Dual Column Cloud Condensation Nuclei Counter (CCN) Single Particle Soot Photometer (SP2) Scanning Mobility Particle Sizer (SMPS) Photo-Acoustic Soot Spectrometer (PASS), 3 Wavelength Humidigraph (3 Relative Humidities with 3 single wavelength nephelometers) Humidigraph (Scanning Relative Humidity with 3 single wavelength nephelometers) Trace Gas Instrument System (Research-Grade) Particle Into Liquid Sampler-Ion Chromatography-Water Soluble Organic Carbon (PILS-IC-WSOC) Particle Soot Absorption Photometer (PSAP), 3 Wavelength Nephelometer, 3 Wavelength Condensation Particle Counter (CPC), 10 nm to >3000 nm particle size range Condensation Particle Counter (CPC), 2.5 nm to >3000 nm particle size range Hygroscopic Tandem Differential Mobility Analyzer (HTDMA) Proton Transfer Mass Spectrometer (PTRMS) 7-Wavelength Aethelometer Weather Transmitter (WXT-520) Aerosol Chemistry Speciation Monitor (ACSM)

MAOS

Page 18: Observations  and Modeling of the Green Ocean  Amazon

“Intensive Airborne Research in Amazonia 2014” (IARA-2014)The ARM Aerial Facility (AAF) in Brazil

Page 19: Observations  and Modeling of the Green Ocean  Amazon

Brazil-Side Organizations

• LBA - Large-Scale Biosphere Atmosphere Experiment, http://lba.inpa.gov.br/lba/

• INPA - National Institute for Research in the Amazon, http://www.inpa.gov.br/

• INPE - National Institute for Space Research, http://www.inpe.br/ingles/index.php

• CTA - Department of Science and Aerospace Technology, http://www.cta.br/

• UEA - University of the State of Amazonas, http://www1.uea.edu.br/

• USP - University of São Paulo, http://www.thefullwiki.org/University_of_Sao_Paulo, http://web.if.usp.br/ifusp/, http://www.master.iag.usp.br/index.php?pi=N

• Links to GPM-CHUVA (http://chuvaproject.cptec.inpe.br/portal/en/index.html), SAMBBA (http://www.ncas.ac.uk/fgam/index.php?option=com_content&task=view&id=194&Itemid=1), Andes-Amazon Initiative (http://www.moore.org/andes-amazon.aspx), Amazon-PIRE (http://www.amazonpire.org/)

Page 20: Observations  and Modeling of the Green Ocean  Amazon

GoAmazon2014: Known and Planned Activities

Cloud Life Cycle ProjectGPM-CHUVA

Leader: Luiz Machado

An Aerosol Life Cycle ProjectT2 → T3 Lagrangian experiment

accompanying IARACoordinator: Jian Wang

NASA Satellite ScienceCoordinators: Loretta

Mickley and Jun Wang More activities evolving(some DOE, some not DOE):

Cloud Life Cycle, Aerosol-Cloud- Precipitation Interactions, Carbon Cycle, international partners, …

Cloud Life Cycle ProjectNSF EOL/SPO Facilities S-POLLeader: Courtney Schumacher

Aerosol Life Cycle ProjectBEACHON

Leader: Alex Guenther

AMFA: DOE AMF Deployment

IARA: DOE AAF Deployment

Aerosol-Cloud-Precipitation Interactions

AeroclimaLeader: Paulo Artaxo

iLEAPS IGAC ACPCPoint of contact:

Meinrat Andreae

GECO: DOE TES Deployment

Leader: Jeffrey Chambers

Page 21: Observations  and Modeling of the Green Ocean  Amazon

Outline of Presentation

• WHY this experiment, part 1?• WHERE will this experiment take place?• WHEN will this experiment take place?• WHAT instrumentation and facilities are part of

experiment?• HOW is the experiment organized?• WHY this experiment, part 2?

Page 22: Observations  and Modeling of the Green Ocean  Amazon

Carbon Cycle - improve Community Earth System Model (CESM) for land-atmosphere processes in the Amazon Basin, including aerosol-cloud-precipitation connections• Objective - Reduce uncertainties in our knowledge of feedbacks between vegetation-

hydrology that underlie the Amazon forest dieback hypothesis. The uncertain range of feedbacks at present leads to large differences in ESM predictions.

• Objective - Response of photosynthesis and transpiration, including BVOC emissions, to changes in the direct and diffuse components of incoming solar radiation, i.e., in the context of current and future scenarios of aerosols and clouds in the Amazon Basin.

Aerosol Life Cycle - accurate modeling of aerosol sources/sinks and aerosol optical, CCN, and IN properties, as affected by pollution of pristine tropical environments• Objective - The interactions of the urban pollution plume with biogenic volatile

organic compounds in the tropics, especially the impact on the production of secondary organic aerosol, the formation of new particles, and biogenic emissions of aerosols and their precursors.

• Objective - Influence of anthropogenic activities on aerosol microphysical, optical, cloud condensation nuclei (CCN), and ice nuclei (IN) properties in the tropics. 

Carbon Cycle - improve Community Earth System Model (CESM) for land-atmosphere processes in the Amazon Basin, including aerosol-cloud-precipitation connections• Objective - Reduce uncertainties in our knowledge of feedbacks between vegetation-

hydrology that underlie the Amazon forest dieback hypothesis. The uncertain range of feedbacks at present leads to large differences in ESM predictions.

• Objective - Response of photosynthesis and transpiration, including BVOC emissions, to changes in the direct and diffuse components of incoming solar radiation, i.e., in the context of current and future scenarios of aerosols and clouds in the Amazon Basin.

Aerosol Life Cycle - accurate modeling of aerosol sources/sinks and aerosol optical, CCN, and IN properties, as affected by pollution of pristine tropical environments• Objective - The interactions of the urban pollution plume with biogenic volatile

organic compounds in the tropics, especially the impact on the production of secondary organic aerosol, the formation of new particles, and biogenic emissions of aerosols and their precursors.

• Objective - Influence of anthropogenic activities on aerosol microphysical, optical, cloud condensation nuclei (CCN), and ice nuclei (IN) properties in the tropics. 

Scientific Questions for GoAmazon2014Note: Non-exhaustive selected list. Further development anticipated.

Carbon Cycle - improve Community Earth System Model (CESM) for land-atmosphere processes in the Amazon Basin, including aerosol-cloud-precipitation connections• Objective - Reduce uncertainties in our knowledge of feedbacks between vegetation-

hydrology that underlie the Amazon forest dieback hypothesis. The uncertain range of feedbacks at present leads to large differences in ESM predictions.

• Objective - Response of photosynthesis and transpiration, including BVOC emissions, to changes in the direct and diffuse components of incoming solar radiation, i.e., in the context of current and future scenarios of aerosols and clouds in the Amazon Basin.

Aerosol Life Cycle - accurate modeling of aerosol sources/sinks and aerosol optical, CCN, and IN properties, as affected by pollution of pristine tropical environments• Objective - The interactions of the urban pollution plume with biogenic volatile

organic compounds in the tropics, especially the impact on the production of secondary organic aerosol, the formation of new particles, and biogenic emissions of aerosols and their precursors.

• Objective - Influence of anthropogenic activities on aerosol microphysical, optical, cloud condensation nuclei (CCN), and ice nuclei (IN) properties in the tropics. 

Carbon Cycle - improve Community Earth System Model (CESM) for land-atmosphere processes in the Amazon Basin, including aerosol-cloud-precipitation connections• Objective - Reduce uncertainties in our knowledge of feedbacks between vegetation-

hydrology that underlie the Amazon forest dieback hypothesis. The uncertain range of feedbacks at present leads to large differences in ESM predictions.

• Objective - Response of photosynthesis and transpiration, including BVOC emissions, to changes in the direct and diffuse components of incoming solar radiation, i.e., in the context of current and future scenarios of aerosols and clouds in the Amazon Basin.

Aerosol Life Cycle - accurate modeling of aerosol sources/sinks and aerosol optical, CCN, and IN properties, as affected by pollution of pristine tropical environments• Objective - The interactions of the urban pollution plume with biogenic volatile

organic compounds in the tropics, especially the impact on the production of secondary organic aerosol, the formation of new particles, and biogenic emissions of aerosols and their precursors.

• Objective - Influence of anthropogenic activities on aerosol microphysical, optical, cloud condensation nuclei (CCN), and ice nuclei (IN) properties in the tropics. 

Carbon Cycle - improve Community Earth System Model (CESM) for land-atmosphere processes in the Amazon Basin, including aerosol-cloud-precipitation connections• Objective - Reduce uncertainties in our knowledge of feedbacks between vegetation-

hydrology that underlie the Amazon forest dieback hypothesis. The uncertain range of feedbacks at present leads to large differences in ESM predictions.

• Objective - Response of photosynthesis and transpiration, including BVOC emissions, to changes in the direct and diffuse components of incoming solar radiation, i.e., in the context of current and future scenarios of aerosols and clouds in the Amazon Basin.

Aerosol Life Cycle - accurate modeling of aerosol sources/sinks and aerosol optical, CCN, and IN properties, as affected by pollution of pristine tropical environments• Objective - The interactions of the urban pollution plume with biogenic volatile

organic compounds in the tropics, especially the impact on the production of secondary organic aerosol, the formation of new particles, and biogenic emissions of aerosols and their precursors..

• Objective - Influence of anthropogenic activities on aerosol microphysical, optical, cloud condensation nuclei (CCN), and ice nuclei (IN) properties in the tropics. 

Page 23: Observations  and Modeling of the Green Ocean  Amazon

Scientific Questions for GoAmazon2014Note: Non-exhaustive selected list. Further development anticipated.

Cloud Life Cycle - development of a knowledge base to improve tropical cloud parameterizations in GCMs• Objective - The transition from shallow to deep cumulus convection during the daily

cycle of the Amazon Basin, with comparison and understanding to other environments.• Objective - The role of landscape heterogeneity—the Manaus urban area as well as the

10-km-scale of river width—on the dynamics of convection and clouds (+carbon cycle)

• Objective - The evolution of convective intensity from severe storms in the dry season to moderate storms in the wet season.

 Cloud-Aerosol-Precipitation Interactions - improvement of parameterizations of aerosol-cloud interactions in climate models• Objective - Aerosol effects on deep convective clouds, precipitation, and lightning

under different aerosol and synoptic regimes, including the roles of aerosols in changing regional climate and atmospheric circulation.

• Objective - Data-driven improvement of parameterizations of aerosol-cloud interactions in the climate models.

Cloud Life Cycle - development of a knowledge base to improve tropical cloud parameterizations in GCMs• Objective - The transition from shallow to deep cumulus convection during the daily

cycle of the Amazon Basin, with comparison and understanding to other environments.• Objective - The role of landscape heterogeneity—the Manaus urban area as well as the

10-km-scale of river width—on the dynamics of convection and clouds (+carbon cycle)

• Objective - The evolution of convective intensity from severe storms in the dry season to moderate storms in the wet season.

 Cloud-Aerosol-Precipitation Interactions - improvement of parameterizations of aerosol-cloud interactions in climate models• Objective - Aerosol effects on deep convective clouds, precipitation, and lightning

under different aerosol and synoptic regimes, including the roles of aerosols in changing regional climate and atmospheric circulation.

• Objective - Data-driven improvement of parameterizations of aerosol-cloud interactions in the climate models.

Cloud Life Cycle - development of a knowledge base to improve tropical cloud parameterizations in GCMs• Objective - The transition from shallow to deep cumulus convection during the daily

cycle of the Amazon Basin, with comparison and understanding to other environments.• Objective - The role of landscape heterogeneity—the Manaus urban area as well as the

10-km-scale of river width—on the dynamics of convection and clouds (+carbon cycle)

• Objective - The evolution of convective intensity from severe storms in the dry season to moderate storms in the wet season.

 Cloud-Aerosol-Precipitation Interactions - improvement of parameterizations of aerosol-cloud interactions in climate models• Objective - Aerosol effects on deep convective clouds, precipitation, and lightning

under different aerosol and synoptic regimes, including the roles of aerosols in changing regional climate and atmospheric circulation.

• Objective - Data-driven improvement of parameterizations of aerosol-cloud interactions in the climate models.

Cloud Life Cycle - development of a knowledge base to improve tropical cloud parameterizations in GCMs• Objective - The transition from shallow to deep cumulus convection during the daily

cycle of the Amazon Basin, with comparison and understanding to other environments.• Objective - The role of landscape heterogeneity—the Manaus urban area as well as the

10-km-scale of river width—on the dynamics of convection and clouds (+carbon cycle)

• Objective - The evolution of convective intensity from severe storms in the dry season to moderate storms in the wet season.

 Cloud-Aerosol-Precipitation Interactions - improvement of parameterizations of aerosol-cloud interactions in climate models• Objective - Aerosol effects on deep convective clouds, precipitation, and lightning

under different aerosol and synoptic regimes, including the roles of aerosols in changing regional climate and atmospheric circulation.

• Objective - Data-driven improvement of parameterizations of aerosol-cloud interactions in the climate models.

Cloud Life Cycle - development of a knowledge base to improve tropical cloud parameterizations in GCMs• Objective - The transition from shallow to deep cumulus convection during the daily

cycle of the Amazon Basin, with comparison and understanding to other environments.• Objective - The role of landscape heterogeneity—the Manaus urban area as well as the

10-km-scale of river width—on the dynamics of convection and clouds (+carbon cycle)

• Objective - The evolution of convective intensity from severe storms in the dry season to moderate storms in the wet season.

 Cloud-Aerosol-Precipitation Interactions - improvement of parameterizations of aerosol-cloud interactions in climate models• Objective - Aerosol effects on deep convective clouds, precipitation, and lightning

under different aerosol and synoptic regimes, including the roles of aerosols in changing regional climate and atmospheric circulation.

• Objective - Data-driven improvement of parameterizations of aerosol-cloud interactions in the climate models.

Cloud Life Cycle - development of a knowledge base to improve tropical cloud parameterizations in GCMs• Objective - The transition from shallow to deep cumulus convection during the daily

cycle of the Amazon Basin, with comparison and understanding to other environments.• Objective - The role of landscape heterogeneity—the Manaus urban area as well as the

10-km-scale of river width—on the dynamics of convection and clouds (+carbon cycle)

• Objective - The evolution of convective intensity from severe storms in the dry season to moderate storms in the wet season.

 Cloud-Aerosol-Precipitation Interactions - improvement of parameterizations of aerosol-cloud interactions in climate models• Objective - Aerosol effects on deep convective clouds, precipitation, and lightning

under different aerosol and synoptic regimes, including the roles of aerosols in changing regional climate and atmospheric circulation.

• Objective - Data-driven improvement of parameterizations of aerosol-cloud interactions in the climate models.

Page 24: Observations  and Modeling of the Green Ocean  Amazon

Outline of Presentation

• WHY this experiment, part 1?• WHERE will this experiment take place?• WHEN will this experiment take place?• WHAT instrumentation and facilities are part of

experiment?• HOW is the experiment organized?• WHY this experiment, part 2?

Page 25: Observations  and Modeling of the Green Ocean  Amazon

An Aerosol Life Cycle ProjectT2 → T3 Lagrangian experiment

accompanying IARA

A more detailed example: What we learned in AMAZE-08 and what we hope

to learn in GoAmazon2014

Page 26: Observations  and Modeling of the Green Ocean  Amazon

Amazonian Aerosol Characterization Experiment (AMAZE-08)

Wet Season of Central Amazônia in January – March 2008

S.T. Martin, M.O. Andreae, D. Althausen, P. Artaxo, H. Baars, S. Borrmann, Q. Chen, D.K. Farmer, A. Guenther, S. Gunthe, J.L. Jimenez, T. Karl, K. Longo, A. Manzi, T. Pauliquevis, M. Petters, A. Prenni, U. Pöschl, L.V. Rizzo, J. Schneider, J.N. Smith, E. Swietlicki, J. Tota, J. Wang, A. Wiedensohler, S.R. Zorn, "An Overview of the Amazonian Aerosol Characterization Experiment 2008 (AMAZE-08)," Atmospheric Chemistry Physics, 2010, 10, 11415-11438

Page 27: Observations  and Modeling of the Green Ocean  Amazon

IsopreneC5H8

α-PineneC10H16

β-CaryophylleneC15H24

OH NO3

O3

Atmospheric Oxidants react with the Biogenic Emissions

Page 28: Observations  and Modeling of the Green Ocean  Amazon

High-volatility molecules in gas phase

Low-volatility molecules in particle phase

Secondary Organic Material (SOM) Contributes to Particle Growth

Page 29: Observations  and Modeling of the Green Ocean  Amazon

SOA Particles of Ozonized α-Pinene

Harvard Environmental Chamber

AMAZE-08 in Central Amazonia

Adapted from Chen et al., Geophys. Res. Lett., 2009, 36, L20806and Shilling et al., Atmos. Chem. Phys., 2009, 9, 771-782.

Similarity Between Mass Spectra Observed in AMAZE-08 and SOA Particles Generated in Environmental Chamber

Page 30: Observations  and Modeling of the Green Ocean  Amazon

Q. Chen, D.K. Farmer, J. Schneider, S.R. Zorn, C.L. Heald, T.G. Karl, A. Guenther, J.D. Allan, N. Robinson, H. Coe, J.R. Kimmel, T. Pauliquevis, S. Borrmann, U. Poeschl, M.O. Andreae, P. Artaxo, J.L. Jimenez, and S.T. Martin, "Mass spectral characterization of submicron biogenic organic particles in the Amazon Basin," Geophysical Research Letters, 2009, 36, L20806.

High-Resolution Mass Spectra

CHNOCH3N2

C2H3O C2H5NC3H7CHNO

CH3N2

C2H3O C2H5NC3H7CHNO

CH3N2

C2H3O C2H5NC3H7

QuadrupoleC-ToFV-ToFW-ToF

QuadrupoleC-ToFV-ToFW-ToF

QuadrupoleC-ToFV-ToFW-ToF

Q-AMSC-ToF-AMSV-mode HR-ToF-AMSW-mode HR-ToF-AMS

CHNOCH3N2

C2H3O C2H5NC3H7

43.543.042.5

0.15

0.10

0.05

0.00

43.543.042.5

0.15

0.10

0.05

0.00

43.543.042.5

0.15

0.10

0.05

0.00

43.543.042.5

0.15

0.10

0.05

0.00

43.2 m/z4

Page 31: Observations  and Modeling of the Green Ocean  Amazon

Dominance of Secondary Organic Material in Submicron Particles

OH NO3

O3

1. SEM

2. AMSO:C of 0.4 to 0.5, consistent with chamber SOA particles

3. CCNMeasured CCN activity accurately predicted using κorganic,SOA from lab results

4. AMSSimilarity of measured mass spectra to those chamber SOA particles

5. AMSAbsence of features for PBAPs

Page 32: Observations  and Modeling of the Green Ocean  Amazon

Reference: Kuhn, U.; Ganzeveld, L.; Thielmann, A.; Dindorf, T.; Welling, M.; Sciare, J.; Roberts, G.; Meixner, F. X.; Kesselmeier, J.; Lelieveld, J.; Ciccioli, P.; Kolle, O.; Lloyd, J.; Trentmann, J.; Artaxo, P.; Andreae, M. O., “Impact of Manaus City on the Amazon Green Ocean atmosphere: Ozone production, precursor sensitivity, and aerosol load,” Atmos. Chem. Phys. 2010, 10, 9251-9282.

But the chemistry can be completely shifted under anthropogenic influences… NOx concentration, SO2/H2SO4 particles

Page 33: Observations  and Modeling of the Green Ocean  Amazon

But the chemistry can be completely shifted under anthropogenic influences… NOx concentration, SO2/H2SO4 particles

RH R· ROO·OH O2

ROOH

RONO2

RO·

ROONO2

NO

NO2

HO2

RO2

Page 34: Observations  and Modeling of the Green Ocean  Amazon

Isoprene Hydroxy-peroxy radical (8 isomers)

OH, O2

NO HO2

OHhydroxylnitrate MVK

MACRhydroxycarbonylHydroxy-

hydroperoxide and other

hydroperoxides

Dihydroxy-epoxide

Pristine Condition

Polluted Condition

But the chemistry can be completely shifted under anthropogenic influences… NOx concentration, SO2/H2SO4 particles

Page 35: Observations  and Modeling of the Green Ocean  Amazon

Outline of Presentation

• WHY this experiment, part 1?• WHERE will this experiment take place?• WHEN will this experiment take place?• WHAT instrumentation and facilities are part of

experiment?• HOW is the experiment organized?• WHY this experiment, part 2?

Page 36: Observations  and Modeling of the Green Ocean  Amazon

Join this Google group to receive email from PI:

http://groups.google.com/group/GoAmazon2014

Websites:

DOE maintained: http://campaign.arm.gov/goamazon2014/. See there a workshop report of July 2011.

PI maintained: http://www.seas.harvard.edu/environmental-chemistry/GoAmazon2014/