Secondary Organic Aerosols Formation and Characterization

Overview Background Formation Modeling Theoretical investigations Chamber experiments

Particulate Matter in the Atmosphere PM affects visibility, climate, health. Inorganic fractions well characterized. Organic fractions are poorly characterized, very complex.

Modeling Atmospheric Aerosol Formation Model aerosol formation to understand its affects on air quality and climate change Accurately represent organic fraction Better characterization chemical composition of atmospheric organic aerosols Better understanding of secondary organic aerosol (SOA) formation, including the role of MW-building reactions (i.e., "accretion reactions”)

Formation of Atmospheric Organic Aerosols Aerosols = liquid or solid particles suspended in a gas (e.g., the atmosphere) Physical state of compound largely dependent on pure-compound vapor pressure (p°L) How can a compound have low/lower volatility? Inherent: compounds emitted as PM Undergo oxidation: VOCs + NOx,O3, •OH → oxidation products Undergo MW-building reactions: oxidation products/ atmospheric compounds→ high-MW products Lowering volatility increases the tendency of a compound to condense, thereby forming PM

Formation of Atmospheric Organic Aerosols OA gas/particle (G/P) partitioning gas/particle (G/P) partitioning high molecular-weight (MW)/ low-volatility products accretion reactions oxidation products -COOH -OH -C=O Biogenic Anthropogenic oxidation Emissions Volatile Organic Compounds

Fundamental Thermodynamics of SOA Formation by Accretion Reaction Ag + Bg Cg Cliq

Mathematical Solution Process Multiple accretion reactions and products from parent compound A: 2A C1 2A C2 + H2O A + B C3 A + B C4 + H2O Mass balance leads to: A and C denote concentrations (µg m-3) N number of accretion products from A

Accretion Reactions of Aldehydes and Ketones Based on work of Jang and Kamens Reaction of 4 n-aldehydes and ketones (C4, C6, C8, C10) 5 Accretion products for each aldehyde/ketone (hydrate, dimer, trimer, hemiacetal, acetal, hydroxy carbonyl, unsaturated carbonyl) Considered same reactions for pinonaldehyde, inputs representative of ambient conditions

Accretion Reactions of Dialdehydes, Methylglyoxal, Diketones

Accretion Reactions of Carboxylic and Dicarboxylic Acids: Ester and Amide Formation Accretion reactions of 5 acids Ester formation w/ MBO, amide formation w/DEA and NH3 Inputs representative of ambient conditions

Results for Carboxylic and Dicarboxylic Acids Predicted OPM as a Function of A0 MBO0 and DEA0= 1 µg m-3 NH3 ≈ 0.1 µg m-3 OPMna = 10 µg m-3 RH = 20%, T = 298 K For malic, maleic, and pinic acids OPM formation is significant For acetic acid, accretion products do not condense into OPM phase Esters and at least 1 amide contribute to predicted level of additional OPM

Implications for Observed OPM Formation in Chamber Experiments MW 256-695 g mol-1 dominant accretion reactions MW 200-900 g mol-1, combination of monomers (Tolocka et al., 2004) MW 250-450 g mol-1 dimers, MW 450-950 g mol-1 trimers and higher oligomers (Gao et al., 2004a,b) OPMna = 0, RH = 50%, T = 298 K Δα-Pinene (µg m-3) Predicted OPM 6 (~1 ppb) 0.15 56 1.7 280 8.9 560 18 840 27 19000 (~3400 ppb) 650

Summary of Dissertation Research Accretion reactions appear to play a role in atmospheric SOA formation Currently, the dominant accretion reactions/products are not known Developed a “first-cut” approach to identifying favorable reactions and estimating their potential contribution to SOA Lot’s of work to be done!

Biogenic Aerosol Chamber Reaction Chamber Ozone Source Cylinder Air CIMS PTRMS Ozone Monitor 2 SO2 Monitor SMPS Filter Sampler UFPC HTDMA SO2 Scrubber Biomass Chamber Humidifier TDCIMS T, RH

Filter Sample Analysis: GC x GC Entire sample passed through two different columns First column usually separates based on volatility, second usually separates based on polarity

GC x GC Spectrum (← ret. time) polarity volatility (→ ret. time) alcohols (← ret. time) polarity aldehydes alkanes volatility (→ ret. time)

Future Plans Look for accretion products in filter samples from chamber experiments and field experiments Use PTR-MS to “track” gas phase species Use GC x GC to analyze filter samples Compare data with thermodynamic model predictions Parameterize reactions to include in regional/global models