The Air-Sea Gas Transfer Velocity

- Approaching it from Multiple Angles

Mingxi Yang, T. Bell, P. Nightingale, J. Shutler

(Additional contributions from B. Blomquist)

Plymouth Marine Laboratory

ESA/EGU/SOLAS Conference, Frascati, Oct 2014

Gas Transfer Velocity (K) Controlled by Resistance on Airside/Waterside – Partitioning Depends on Solubility (α)

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Ka = [1

ka+

1

αkw]−1 ≈ ka Large α

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Kw = [1

kw+α

ka]−1 ≈ kw Small α

Resistance on Airside/waterside analogous to two resistors in series

ra=1/ka

rw=1/kw

Highly soluble gases limited on airside

Sparingly soluble gases limited on waterside

7 m/s and 20 °C, COARE model

Momentum/heat transfer airside controlled

Acetone subject to both airside & waterside control

Motivation

Approximate Uncertainty 3 < U < 10 m/s U > 15 m/s ka 20% 50%

kw 30% 80%

ktangential 20% 50%

kbubble 20% 60%

• Reduce uncertainties in k (airside and waterside controlled gases), especially in high winds

• Improve process level understanding in gas transfer

ApproachMeasure k of multiple gases with varying solubility in

conjunction with observations of waves, bubbles, etc. Example: High Wind Gas Exchange Study (HiWinGS)

HiWinGS Cruise, Oct/Nov 2013

St Jude Storm25~28 Oct, 2013

Guardian

Telegraph

List of Observations

PML Contribution:

Directly quantify the air-sea transport of methanol & acetone

- Air concentration : PTR-MS w/ isotopic standard (Yang et al. ACP, 2013)

- Water concentration: PTR-MS w/ membrane inlet (Beale et al. ACA, 2011)

- Air-sea flux: Eddy Covariance w/ PTR-MS (Yang et al. ACP, 2013, 2014)

Sonic anemometer (10 Hz)

Motion sensor (~15 Hz)

Gas inlet to PTRMS housed in lab van

PML Eddy Covariance System

On Ship’s Foremast (~20 m amsl)

Methanol & Acetone Concentrations and FluxFrom High Resolution Proton-Transfer-Reaction

Mass Spectrometer (PTR-MS)

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H3O+ +CH3OH →H2O+CH3OH ⋅H

+

H3O+ +CD3OH →H2O+CD3OH ⋅H

+

• Measuring at ~2.2 Hz• Soft chemical ionization• Isotopic standards added at inlet tip

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Flux =Ca’W ’

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Ka ≈ Flux /(Cw /α −Ca )

Eddy covariance flux

Wind velocity corrected for ship motion (Edson et al 1998)

Total transfer velocity from air perspective

- Yang et al PNAS 110, 50, 20034–20039, 2013- Yang et al ACP 14, 7499-7517, 2014

Friction velocity consistent with COARE prediction

As is sensible heat

Measurements better described by COARE

model V3.5 than V3.0, especially in high winds

Greater scatter in calmer conditions, when winds

often came from the side of the ship (minor flow

distortion)

Momentum Transfer

Reduced sensible heat transfer during

25 Oct Storm

- Sea spray/precipitation attenuates sensible

heat flux?

Methanol & Acetone fluxes from air to sea Close to bulk predictions (~18% relative RMS error)

Transfer Velocities of Methanol & Acetone (Ka = Flux/ΔC)in general agreement with COARE Model on the mean

(some deviations in very high winds…)

Asymmetry between Airside and Waterside Transfer

Diffusion & Micro turbulence

Ca,0

Cw,0

Ca

Cw

Diffusion & Micro turbulence

Air

Water

Modified from Jaehne and Haussecker, 1998

Turbulence

Turbulence

~ 1 mm

~ 0.1 mm

Zw

Airside transfer (ka) significantly limited by both turbulent (aerodynamic) resistance and molecular diffusive resistance

Waterside transfer (kw) mostly limited by molecular diffusion/micro turbulence

KHeat ~12% higher than KMeOH

- Heat has higher diffusivity in air

KAcetone ~28% lowerthan KMeOH

- Acetone has lower solubility in water and lower diffusivity in air

Acetone Transfer Subject to Airside +Waterside Resistance- Estimation of kw by Difference

Ka : Total transfer velocity ka : Airside transfer velocitykw : Waterside transfer velocityα : Dimensionless solubility

At HiWinGs mean U10n of 12 m/s, we get:

kw = 9.1±4.3 cm/hr, normalized to Scw = 660

kw660 = 15.9±7.4 cm/hr

kw =1/(α(1/Ka – 1/ka))

Gas Kw660 (cm/hr) at U10n=12 m/s

Reference

Acetone 15.9±7.4 This work

DMS 18~22 Yang et al. 2011

Dual Tracer 34 Nightingale et al 2000

Dual Tracer 37 Ho et al 2006

CO2 48 McGillis et al 200114C 39 Sweeney et al 2007

Indirectly estimated kw close to kDMS Tangential transfer

Additional bubble-mediated transfer for less soluble gases

Conclusions thus far from HiWinGS [Yang et al. accepted in JGR Oceans]

• Turbulent transfer of momentum, sensible heat, methanol, and acetone largely follow expected trends up to U ~20 m/s– Reduction in heat/organics transfer in higher winds, possibly related to sea

spray/precipitation?

• Airside transfer velocity (ka) from methanol lower than that of sensible heat– Explained by difference in airside diffusivity

• Waterside transfer velocity (kw) indirectly estimated from measurements of acetone transfer – Close to previous estimates of kDMS (tangential transfer)

– Much lower than kw of less soluble gases

OutlookExpand the range of proxy tracers measured

to better understand physical processes

– Sparingly soluble• Carbon monoxide

(Blomquist et al. AMT, 2012)

• Terpenes?

– Intermediate solubility

• Acetaldehyde (Yang et al. ACP 2014)

• Organohalogens?

– Surface reactive• Ozone (e.g. Bariteau et

al. 2011)• Sulfur dioxide (e.g.

Faloona et al. 2010)

– Heat• Modified Controlled

Flux Technique (e.g. Nagel et al. 2014)Modified from

Wanninkhof et al. 2009

Sol. Sc No.

Flux

ΔC

K

Outlook (cont’)Remote sensing of other factors that control k

(Coincident to in situ multi-gas k measurements)

1. Satellite altimeter backscattering more directly related to surface turbulence than wind speed– EC kDMS correlated to Ku band backscattering; better correlation with difference

between Ku band and C band (Goddijn-Murphy et al. 2012, 2013)– How to increase overlap between altimetry data and in situ k observation?

• Copernicus programme: Sentinel-3 mission• Aircraft? Geostationary satellite?

OSSPRE CruiseU. Heidelberg, U. Washington

2. Mean squared wave slope• Scanning laser slope gauge (e.g. Bock

and Hara, 1995; Frew et al 2004)

• Reflective stereo slope gauge & medium angle slope gauge (e.g. Kiefhaber et al 2011)

• Accounts for surfactant effect

Questions & Comments?

More Insights from HiWinGs in the Near Future

• DMS– Comparison of kDMS with previous high wind measurements (e.g. SO

GasEx 2008, Knorr 2011). Suppression in high winds?

• CO2

– Intercomparison of two closed-path sensors and comparison with previous measurements. Which wind speed dependence?

• Multi-gas Comparisons– Difference between kDMS and kCO2 explained by bubbles?– Influence of wave state, bubble, and sea spray on waterside and

airside transfer?– …

UH, NOAA

PMLSonic anemometer

UH, NOAA

PML, UCSDSampling line

Instrument Setup

Airmass Back Trajectories (5-day HYSPLIT)

Sensible Heat Flux Mostly Consistent with COARE Model

Mean HiWinGs Cospectra Demonstrate Expected Behaviors of

Atmospheric Turbulence

Peak at 0.1~0.2 Hz due to wind-wave interaction or imperfect motion correction?

Attenuation of sensible heat transfer related to sea spray?

U’W’

U’T’

Higher atm. Acetone & methanol concentrations further south,

esp. in southerly/westerly winds

High degree of correlation between the two suggests

common sources (e.g. terrestrial emission)

Lower concentrations

In high humidity

Gas solubility affects bubble-mediated transport (kb)

NOAA-COARE Gas Transfer Model

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kb =Vo fwhα−1[1+ (eαSc−1/ 2)−1/1.2]−1.2

: Ostwald solubilityfwh: Whitecap fraction (~u3)

Woolf (97) model:

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kw = 360000u*(ρw /ρ a)−1/ 2[hwSc

1/ 2 + κ −1 ln(0.5 /δw )]−1 + Bkb

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hw =13.3/(Aφ)

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ka =100u*[13.3Sca1/ 2 +CD

−1/ 2 − 5 + 0.5κ −1 ln(Sca )]−1

Waterside

Airside

A & B are empirical constants

Motivation — Large Divergence in kw in High Winds

Obs rare in stormy seas

Existing obs suggest solubility dependence in kw

kw higher for CO2 than for dual tracer (not explained by COARE model)

Yang et al., JGR, 2011 & Unpublished Data

Motivation (cont’) —Why Apparent Attenuation of kDMS in High Winds?

Bell et al., ACP, 2013

S. Ocean, 2008N. Atlantic2011