understanding the hygroscopic properties of black carbon ...€¦ · understanding the hygroscopic...
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Understanding the Hygroscopic Properties of Black Carbon/Organic Carbon Mixing States:
Connecting Climate and Health Impacts of Anthropogenic Aerosol
Akua Asa-Awuku University of Maryland, College Park
Dept of Chemical and Biomolecular Engineering
EPA Black Carbon Webinar Series, Monday, November 21st, 2016
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IPCC, 2014
Clouds contribute the greatest uncertainty in climate predications
The interactions of BC with clouds are not well constrained
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RELEVANT PROPERTIES OF COMPLEX CCN
Cloud condensation nuclei (CCN) activate and become cloud droplets.
The ability to be CCN depends on particle size and composition
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RELEVANT PROPERTIES OF COMPLEX CCN
Cloud condensation nuclei (CCN) activate and become cloud droplets.
The ability to be CCN depends on particle size and composition
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The more complex the aerosol source (as with combustion/BC sources) the more difficult it becomes to
characterize the changing chemical and physical properties of the CCN.
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Particulate Matter (PM 2.5)
The ability of aerosol to uptake water (hygroscopicity) has the potential to impact both climate and health
Aerosol droplet growth affects lung deposition rates and human health
Aerosols impact cloud formation and climate.
Asa-Awuku Research Group Linking Climate & Health:
Composition? • Sources? • Emission Rates? • Toxicity? • Number Concentration? • Particle Size?
Carbonaceous Aerosol
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CHASSIS DYNAMOMETER ENVIRONMENTAL CHAMBER
MIXING STATE FLOW TUBE
NEAR-ROAD TESTING SHIP EMISSIONS
Field Testing
Lab Tests
Real World Simulations
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(2) Characterize Changes in Physical and Chemical Properties that can alter perceived Hygroscopicity of sources
(1) Provide Quantitative and Fast Measurement Techniques for Real-World Sources
(3) Refine Analysis Methods for complex CCN Mixing States
Condensation
Source: NASA : Black Carbon Cloud Droplets (artist rendition)
OUR APPROACH TO COMPLEX HYGROSCOPIC PARTICLES
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A Unique Online , P?·•:,,..1n r-....•·="··• D~
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fOY.!RQOtll!Pi~ Atmos. Chem. Phys. Discuss.., 14, 12555-12589. 2014 www.abnos-chem-plly~iscuss.netl114/12555/20141
doi:10.51S4/acpd-14-12555-2014 @ Au:thor(s) 2014. CC Attrfuution 3.0 L!ioonse.
Th s d1scuss1on pape as/has been under review for the Journal Atmosphenc Chemistry and Phys cs ACP Please refer to the corresponding final paper m ACP if available
Exp1erimentally meas1ured morphology of biomass burni1ng a1erosol a1nd its impacts on CCNI ability
1 2 1 2 2M. fGiordano · , C. Espinoza • , and A. Asa-Awuku1•
1 Department of Chemical and Environmental Engineering, UniVersity of CaJifornia - RiVerside, RiVersldel Californ.ial USA 2College of Engineefl'iing - Center for Environmental Research and Technology (CE-CERT) 1
Hiversldej CAt USA
Received: 1o April 20 14 - Accepted: 17 Ap:rll 20114 - Published: 16 IMay 201 4
Cormspondence co; A. Asa-Awuku (akua@,engr.ucr.e.du)
Publi-she.d by COpernicus Publications on behalf of lhe European Geosclence.s Union.
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Mixing State Projects
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Motivation • CCN data sets from ambient and
environmental chamber studies can consist of complex mixtures of organic and inorganic aerosols
• Common assumptions – Doubly charged aerosols – Uniform composition Single fit
• Multiple activation curves…? – Different components? – Mixing state? Type / Extent?
Complex mixtures?
?
α-Pinene / Diesel Exhaust Mixture Environmental Chamber CCN
activation data data from Asa-Awuku et al. GRL 2009
GOAL: Improve experimental analysis techniques of CCN of complex mixtures
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Recreating Activation Curves: Known Mixtures
CCNC was operated between 0.2 and 1.1 SS%
Stream 1 Stream 2 Organic* Inorganic Salt**
Vu et al., in prep *Organic: Succinic Acid, C4H6O4 **Inorganic Salt: Ammonium Sulfate, (NH4)2SO4, Sodium Chloride, NaCl
Hygroscopicity Continuous-flow thermal gradient
diffusion Cloud Condensation Nuclei Counter (CCNC)
Particle Size Scanning Mobility
Particle Sizer (SMPS) 102 Size bins, 7.37 to 224.7 nm
Scan time: 135 sec
Atomizers
FLOW TUBE Ø=7.08”, length 78”, ~50.3 liters
SMPS/CCNC
Electrostatic
CCNC
Classifier (TSI 3080)
CPC (TSI 3772)
(DMT)
D
A M
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Atmospheric aerosols are often mixed and
comprised of multiple components
External mixture
More hygroscopic
Less Hygroscopic
Internal mixture
?
Mixing States: Internal / External Mixtures
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a 𝜿𝜿𝑨𝑨𝑨𝑨 = 𝟎𝟎. 𝟔𝟔𝟔𝟔
Aerosol mixing can be observed in CCN activation data and can be
revisited in complex aerosol data sets to understand the extent of mixing
𝜿𝜿𝑨𝑨𝑨𝑨 = 𝟎𝟎. 𝟐𝟐𝟐𝟐
• slightly soluble organic: C4H6O4 (SA) • soluble inorganic: (NH4)2SO4 (AS)
SS 0.8%
Change in mixing state: external (dry) internal (wet)
Modifying Mixing States
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Organic and Combustion Aerosol Mixtures As combustion aerosols internally mixes with the organic material, the
BC CCN activity is modified
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Experimental CCN analysis techniques of known mixtures – Internal Mixtures
• Single activation curve, reflective of internally mixed multicomponent aerosols
– External Mixtures • Multiple activation curves consistent with externally mixed aerosols of
varying solubility, 𝜼𝜼-Kohler to infer plateau height – Flow tube may be used to control mixing states
• Results suggest aerosol water as a significant factor • Under dry conditions, the aerosols maintained an external mixture and
multiple activation curves were observed to be constant • Under humid conditions, external mixing was initially observed; however,
the aerosol water promoted internal mixing and the activation curves were observed to converge into a single curve
Aerosol mixing can be observed in CCN activation data and can be revisited in complex aerosol data sets to understand the extent of mixing
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Emissions Projects
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Higher speeds produce water-soluble particlesW
ater
Inso
lubl
e M
ass F
ract
ion
B16- Toyota Camry
70 MPH 50 MPH 30 MPH
E10-
• The chemical composition of aerosol from steady-state emissions is NOT the same as the emissions tested on driving cycles.
• This is true for Varying Fuels, Vehicles, and Cycles
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Mobile Atmospheric Chamber (MACh) Effect of Aging on CCN Activity Freshly emitted gasoline vehicle exhaust is hydrophobic and not
CCN active (Vu et al. AS&T 2015)
Physical and chemical changes with atmospheric aging Vehicle emissions are a source of Volatile Organic Compounds (VOCs) that can act as Secondary Organic Aerosol (SOA) precursors
Effect of photochemical aging of gasoline emissions derived from real world driving conditions on CCN activity is currently not well understood
Objective: Integrate fresh tailpipe measurements to aged vehicle emissions characterization
Vehicle Emissions
Atmospheric Processes
Aerosol-Cloud-Climate Interactions
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Other Principle Investigators Georgios Karavalakis, Thomas Durbin,
Graduate Students (Current and Former) Diep Vu, Patrick Roth, Pedro Piqueras, Emmanuel Fofie, Ashley Vizenor, Linh Tong,
Daniel Short, Michael Giordano ★ Undergraduates ★ Tyler Berte, Taylor Stenehjem, Carola Acurio, Bibiana Lopes, Justin Tao, Dennis Nguyen, Luis Perez, Chun Yu
(“Jimmy”) Liang
Technical Support / Engineering Kurt Bumiller, David Cocker, Mark Villela, Michelle Ta, Daniel Gomez, Kevin Castillo
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