Using ISORROPIA II to predict heterogeneous chlorine chemistry

Jessica D. Haskins1 (jhask@uw.edu), L. Jaegle1, F. Lopez-Hilfiker1, B.H. Lee1, V. Shah1, P. Campuzano-Jost3, J. Schroder3, J. Dibb 4, D. Day3,

M. Fiddler5, J. Green5, J. Holloway2, A. Sullivan6, P. Veres2, R. Weber7, S.S. Brown2, J. Jiménez3, and J.A. Thornton1

B.9

II . ISORROPIA II Simulations

IV . Chlorine Partitioning: Observed & Predicted

ISORROPIA II Results:

I. Introduction

Heterogeneous chlorine chemistry in the troposphere can impact:

- long range transport of pollutants- oxidant budget of the atmosphere - sulfate & nitrate aerosol mass- oxidation of VOCs (including CH4)

• Accurately predicting the amount of fine mode chloride, nitrate, and particle liquid water in is paramount in dynamically parameterizing this chlorine chemistry.

• ISORROPIA II could be used to predict acid displacement of HCl in GEOS-Chem & dynamically predict ClNO2 but its ability to do so needs to be validated

N2O5(g) Cl- (2-Φ) HNO3 (g) ClNO2 (g)γ N2O5 Φ

H2ONO2+ (aq) + H2O (l) H3O

+ (aq) + HNO3 (aq) k3

H2ONO2+ (aq) + X- XNO2 + H2O(l)

k4

N2O5 (aq) + H2O (l) H2ONO2+ (aq) + NO3

- (aq)k2f

k2b

N2O5 (g) N2O5 (aq) k1

Mechanism of ClNO2 formation :

Φ (ClNO2) = 1 +[H2O (l)]

[Cl-]

k3

k4

-1

γ (N2O5) = A k2f 1 -[H2O (l)]

[NO3-]

+[NO3

-]

[Cl-]+ 1

k3

k2b

k4

k2b

-1

Fraction of Total in Particle

Fraction of Total in Gas Phase

HCl + Cl-

HNO3 + NO3-

NH3 + NH4+

SO42-

+ trace species

(Na+, …)

ISORROPIA II

Temperature

Relative Humidity

Pressure

NO3-

SO42 -

Na+ NH4+

OH-

Cl-

H+

HCl (g)

HNO3 (g)

NH3 (g)

Keq(HCl) =

Keff(HCl) =

• At equilibrium, the effective equilibrium constant for chlorine partitioning is given as:

• But, there is large uncertainty in the value of Henry’s law/effective equilibrium constants for HCl that could impact predicted chlorine partitioning

• Goal: Test ISORROPIA II’s ability to correctly partition chloride and nitrate between it gas and particle phases using the WINTER 2015 aircraft campaign data collected on 13 Flights from February 2rd, 2015 – March 13th, 2015

• Campaign separately collected gas & aerosol composition data, allowing the validation of ISORROPIA II outputs, given bulk inputs

Simulation Inputs Comments

Base (v0) Total Chloride = CIMS HCl + AMS pCl-

Total Ammonium = iterated NH3 + AMS pNH4+

Total Nitrate = CIMS HNO3 + AMS pNO3-

Total Sulfate = AMS pSO42-

* No NH3 measurement was made during the campaign, so total ammonium was adjusted until the AMS pNH4

+ measurement matched the model output. Note: AMS pCl-measurement does NOT include sea salt contributions

HClsensitivity (50_HCL)

Total Chloride = ± 50% CIMS HCl + AMS pCl-

Total Ammonium = iterated NH3 + AMS pNH4+

Total Nitrate = CIMS HNO3 + AMS pNO3-

Total Sulfate = AMS pSO42-

* Uncertainty in HCl measurements (typically 90% of the total chloride passed to the model) is reported to be 50%. So, the model was run with ± 50% HCl reported to understand the predicted partitioning’s sensitivity to measurement uncertainty.

Iterated pCl-

(pCl_it)

Total Chloride = CIMS HCl + iterated pCl-

Total Ammonium = iterated NH3 + AMS pNH4+

Total Nitrate = CIMS HNO3 + AMS pNO3-

Total Sulfate = AMS pSO42

* Since sea salt contributions are neglected by the AMS, pCl- was iterated until the CIMS HCl measurements were matched, to estimate how much submicron particle chloride is needed to explain the observed partitioning

IV. Observed Chlorine Budget

• ISORROPIA II tends to over predict particle chloride, and under predict gas phase HCl, while the nitrate partitioning shows generally good agreement (as described in Guo et al., 2016)

V. Accounting for Sea-Salt

Maritime < 1.5 km Total Mass: 1043 pptv

Continental < 1.5 km Total Mass: 373 pptv

Concentration (pptv)

HOCl: 2.4%

ClNO2, 2.4%

Submicron pCl, 15%

Particle Cl-,

41.7%

HCl, 55.2%

HCl (g): Median 206 ppt

HOCl (g): Median 8.9 ppt

ClNO2 (g) : Median 2.1 ppt

Particle Cl- : Median 155.5 ppt (0.23 μg m-3)

• The total median boundary layer chlorine budget is dominated by gas phase HCl and particle chloride (<4 μm)

• Submicron chloride is a much larger proportion of the continental budget than it is in marine environments.

• ClNO2 and HOCl are not insignificant, especially in the marine boundary layer

• HCl measurements show point sources from power plants over land, and a broad elevated background over the ocean (top)

• Ratios of total particle chloride to sodium (< 4μm) show broad depletion of chloride with respect to the sea-water ratio, suggesting secondary chemical production of HCl over the ocean, via equilibrium partitioning (bottom)

• The GEOS-Chem halogen model can’t currently capture this trend

• Measurement uncertainty in particle chloride and HCl is not enough to explain the model’s overestimate of particulate chloride and underestimate of gas phase HCl

Fine particle pH & Chlorine Partitioning

• Largest Model-Measurement differences occur at high relative humidity conditions, when significantly more chloride is predicted to be in the particle, but not observed

• Difference in amount of particle chloride expected is not significant enough to perturb particle pH, but could be explained by “missing pCl” source from fine mode sea-salt that the AMS cannot detect

• Adding only a slight amount of particle chloride, accounting for the “missing sea-salt” the AMS cannot detect in the fine mode can bring the chlorine partitioning to agreement (top)

• The nitrate partitioning is NOT significantly impacted by adding the necessary particulate chloride, but actually slightly improves model-measurement agreement across the whole campaign (right)

• There is excess Na+ < 4 μm compared to the estimated submicron Cl- added in 99.5% of the campaign (bottom)

Simulation Base Iterated

pCl

PILS

Median pCl-

(μg m-3)

0.021 0.097 0.0624

Median % Submicron Cl-by mass

5.77% 13.2% 12.5%

Median % in particle (vs. gas phase)

4.38% 10.9% 8.43%

Median NH3(pptv)

26.5 21.5 --

AMS ± 35%

ISORROPIA II ± 50% HCl

This work is supported by a 2015 EPA STAR fellowship #11916206. The WINTER campaign is supported by NSF Award #1360745.

Author Affiliations : 1 University of Washington; Seattle, WA, 2 NOAA; Boulder, CO, 3 University of Colorado; Boulder, CO, 4 University of New Hampshire; Durham, NH , 5 North Carolina A&T State University; Greensboro, NH, 6 Colorado State University, Fort Collins, CO, 7 Georgia Institute of Technology; Atlanta, GA

VII. Acknowledgements

VI . Conclusions & Future Work

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• ISORROPIA II shows some skill at correctly predicting chlorine partitioning when compared to WINTER measurements, taking into account measurement caveats

• Ongoing work investigating equilibrium constant used for chlorine partitioning

• Adding a separate particulate fine mode chloride tracer (as is done with particulate nitrate), would allow for the prediction of equilibrium partitioning of HCl (shown here to be significant ) and could be used to dynamically parameterize ClNO2 formation in GEOS-Chem. WINTER measurements could be used to constrain these new HCl & ClNO2 formation pathways

• Other halogen projects underway: Verifying HOCl concentrations in GEOS-Chem from WINTER campaign data (could impact SIV oxidation shown by Chen et al., 2017)

Aqueous Chloride Model-Measurement Agreement (RF 8)

Aqueous Nitrate Model-Measurement Agreement (RF 8)

Observations of HCl (g)

3.50

2.63

1.76

0.89

0.02

Cl- /

Na+

Rat

io b

y M

ass

Enhanced

Depleted

Displaced Particle Chloride

Environmental Conditions

Particle Chloride

Percentage Cl- in Submicron of Total

New Aqueous Nitrate Measurement-Model Agreement

Estimated pCl-AMS pCl-

Total pCl- <4μm

ISORROPIA pNO3-

AMS pNO3-

Over Ocean

Over Land

% E

stim

ate

d

sub

mic

ron

pC

l- Estimated pCl- < 1μm

x10 -8

x10 -8

KEQ

(M2

atm

-1)