Enhancing Surface Methane Fluxes from an

Supporting Information

Enhancing Surface Methane Fluxes from an Oligotrophic Lake: Exploring the Microbubble Hypothesis

Daniel F. McGinnis1,2,*, Georgiy Kirillin1, Kam W. Tang3, Sabine Flury1, Pascal Bodmer1, Christof Engelhardt1, Peter Casper1 and Hans-Peter Grossart1

1 2

Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany

Institute F.-A. Forel, Section of Earth and Environmental Sciences, Faculty of Sciences, University of Geneva, Geneva, Switzerland

3

Department of Biosciences and Centre for Sustainable Aquatic Research (CSAR), Swansea University, Swansea, UK

13 Pages Pg S2 – S3: Supplemental methods: Meteorological sensor specifications and turbulent kinetic energy dissipation Pg S3– S12: 9 Figures Corresponding Author * Corresponding Author, [email protected], +41 22 379 0792 University of Geneva, Battelle D, Room 211, 7 route de Drize, 1227 Carouge (Geneva), Switzerland S1

Supplemental Methods Weather station specifications The wind speed/direction, air temperature and humidity data were obtained from the Vaisala Weather Transmitter WXT520 (https://store.vaisala.com/eu). Data are measured and reported every 1 minute. The sensor specifications are Wind Speed Range Accuracy Output resolutions and unit

0 – 60 m s-1 ±3% at 10m s-1 0.1 m s-1, 0.1 km h-1

Wind Direction Accuracy Output resolution and unit

±3° 1o

Relative Humidity Range Accuracy Output resolution and unit

0 – 100% RH ±3% RH within 0-90% RH, ±5% RH 90-100% RH 0.1% RH

Air Temperature Range Accuracy for sensor at +20 °C Output resolutions and unit

-52 – +60 °C ±0.3 °C 0.1 °C

Turbulent kinetic energy (TKE) dissipation. The velocity structure function D(z,r) = [(v(z)-v(z+r))2]

(1)

was calculated from the HR-Aquadopp data and was used to estimate total kinetic energy dissipation rate.see 1 Here, v(z) is the along-beam velocity fluctuation at distance z, r is the depth range of the dissipation estimation, square brackets denote time averaging. Three estimations of the velocity fluctuations were determined by extracting the mean velocity value for the averaging periods of 10, 20, and 30 min. Three values of the maximum estimation range for the velocity correlation r = 0.4, 0.5, and 0.6 m were tested, covering the range recommended by Wiles et al. 1 for weakly stratified turbulence. The TKE dissipation rate  was estimated by fitting the equation

S2

Cv-3D(z, r)3/2 = rε(z) + Noise.

(2)

Here, the constant Cv = 31/3.see e.g. 2 The fitting constant Noise representing the average effect of the acoustic noise on the velocity fluctuations was used for the goodness-of-fit check, using the condition Noise > [Cv-3D3/2]

(3)

to discard corresponding  values with subsequent interpolation between the neighboring values. A further quality check was performed by comparison of the 27 arrays of the TKE dissipation rate calculated from the three HR-Aquadopp beams with three different values of r and three averaging periods. The discrepancy between the different estimations did not exceed 10%. The  estimations based on the averaging time of 20 min and r = 0.4 m had a minimum number of bad values according to the Noise condition. Therefore, they were adopted for further analysis instead of an average among the 27 estimations. 1. Wiles, P. J.; Rippeth, T. P.; Simpson, J. H.; Hendricks, P. J., A novel technique for measuring the rate of turbulent dissipation in the marine environment. Geophys. Res. Lett. 2006, 33, (21), L21608. 2. Lien, R. C.; D'Asaro, E. A., The Kolmogorov constant for the Lagrangian velocity spectrum and structure function. Physics of Fluids 2002, 14, 4456-4459.

S3

Figure S1. Bathymetric map of Lake Stechlin. Units of depth contours are in meters.

S4

Figure S2. Picture of floating chamber, tubing, and listed dimensions.

S5

17:04

2

3

4

5

6

7

8

10:19

4

5

6

7

8

9

04:44

2

3

4

5

6

20:20

2

3

4

17:06

Transect 10 Fit

10:21

Transect 7 Fit

04:46

Transect 4 Fit

20:22

Transect 1 Fit

17:08

[CH4]_ppm [CH4]_ppm

0.99658

17:10

10:29

Value -1.91793E9 780.74625

17:12

Value -2.75116E9 1119.93628

10:27

Intercept Slope

0.99919

04:54

Value -1.2821E9 521.91561

20:28

04:52

Intercept Slope

Intercept Slope

10:25

[CH4]_ppm [CH4]_ppm

Adj. R-Square

04:50

[CH4]_ppm [CH4]_ppm

Adj. R-Square

20:26

Value -9.10758E8 370.75004

0.99767

0.99588 Intercept Slope

Adj. R-Square

10:23

04:48

20:24

[CH4]_ppm [CH4]_ppm

Adj. R-Square

[CH4]_ppm [CH4]_ppm [CH4]_ppm

[CH4]_ppm [CH4]_ppm

18:59

7.0 6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0

12:35

2

19:01

19:03

Transect 11 Fit

[CH4]_ppm [CH4]_ppm

19:07

Intercept Slope

23:25

Value -1.93795E9 788.89566

12:43

Value -2.74041E9 1115.56134

06:35

Value -6.91781E8 281.60915

19:09

0.99328

Intercept Slope

12:41

Adj. R-Square

19:05

12:39

[CH4]_ppm [CH4]_ppm

3

23:23

0.99594

Intercept Slope

06:33

23:21

Value -1.32741E9 540.36022

0.98455


Adj. R-Square

06:31

23:19

[CH4]_ppm [CH4]_ppm

Adj. R-Square

Adj. R-Square

12:37

Transect 8 Fit

06:29

Transect 5 Fit

23:17

Transect 2 Fit

4

5

6

7

8

9

06:27

2

3

4

23:15

2

3

4

5

[CH4]_ppm [CH4]_ppm [CH4]_ppm

[CH4]_ppm

[CH4]_ppm

[CH4]_ppm

[CH4]_ppm

S6

[CH4]_ppm

Figure S3. Slopes for CH4 chamber readings. [CH4]_ppm

20:28

2

4

6

8

15:16

2

3

4

5

6

7

8

09:20

3

4

5

01:38

2

3

4

5

6

20:30

20:34

[CH4]_ppm [CH4]_ppm

20:36

Intercept Slope

0.9989

15:26

20:38

Value -2.40767E9 980.10821

15:24

Value -2.50514E9 1019.78731

09:28

Value -1.20774E9 491.64572

01:46


15:22

Adj. R-Square

15:20

[CH4]_ppm [CH4]_ppm

09:26

Intercept Slope

01:44

Value -1.53028E9 622.94589

0.99334


Adj. R-Square

09:24

[CH4]_ppm [CH4]_ppm

Adj. R-Square

01:42

[CH4]_ppm [CH4]_ppm

Adj. R-Square

20:32

Transect 12 Fit

15:18

Transect 9 Fit

09:22

Transect 6 Fit

01:40

Transect 3 Fit

[CO2]_ppm

[CO2]_ppm

[CO2]_ppm

[CO2]_ppm

[CO2]_ppm [CO2]_ppm

17:05

[CO2]_ppm [CO2]_ppm

17:07

17:11

10:25

17:13

Transect 10 Fit

Value 1.94276E10 -7908.55615

10:23

Value 1.0333E10 -4206.34754

17:09


10:21

Adj. R-Square

17:03

320

330

340

350

360

370

380

390


Transect 7 Fit

04:50

Value 1.0343E10 -4210.42981

04:48


04:46

[CO2]_ppm [CO2]_ppm

Adj. R-Square

20:29

17:15

17:17

10:27

04:52

20:27

Transect 4 Fit

20:25

Value 7.35023E9 -2992.12169

20:23


20:21

[CO2]_ppm [CO2]_ppm

Adj. R-Square

Transect 1 Fit

Adj. R-Square

10:19

355

360

365

370

375

380

04:44

380

390

400

410

20:19

370

380

390

400

[CO2]_ppm [CO2]_ppm

19:02

[CO2]_ppm [CO2]_ppm

0.99324

19:04

Intercept Slope

0.98711

Value 1.82221E10 -7417.83099

06:32

19:06

Value 1.46438E10 -5961.16127

12:39

Transect 5 Fit

23:23

Transect 2 Fit

19:08

06:36

23:25

19:12

12:43

19:10

Transect 11 Fit

12:41

Transect 8 Fit

06:34

Value 4.56643E9 -1858.89307

23:21

Value 9.33745E9 -3801.0764

0.92576

23:19

Intercept Slope

Intercept Slope

12:37

Adj. R-Square

19:00

350

360

370

380

390


06:30

[CO2]_ppm [CO2]_ppm

Adj. R-Square

23:17

[CO2]_ppm [CO2]_ppm

Adj. R-Square

Adj. R-Square

12:35

390 385 380 375 370 365 360 355 350 345

06:28

400

405

410

415

23:15

370

380

390

400

[CO2]_ppm [CO2]_ppm [CO2]_ppm

[CO2]_ppm [CO2]_ppm [CO2]_ppm [CO2]_ppm

S7

[CO2]_ppm

Figure S4. Slopes for CO2 chamber readings. [CO2]_ppm [CO2]_ppm

20:32

20:34

Value 1.78038E10 -7247.52034

15:20


20:30

[CO2]_ppm [CO2]_ppm

Adj. R-Square

20:28

340

350

360

370

380

390

15:18

Value 1.63801E10 -6667.99827

09:26

Value 8.39072E9 -3415.6808

09:24


09:22

Adj. R-Square

15:16

390 385 380 375 370 365 360 355 350 345

0.97296

01:44

Value 1.0746E10 -4374.45535

01:42

[CO2]_ppm Intercept [CO2]_ppm Slope

Adj. R-Squa

09:20

370

375

380

385

390

395


01:40

[CO2]_ppm [CO2]_ppm

Adj. R-Square

01:38

380

390

400

410

20:36

Transect 12 Fit

15:22

Transect 9 Fit

09:28

Transect 6 Fit

01:46

Transect 3 Fit

20:38

15:24

09:30

01:48

Figure S5. Contour showing the onset of penetrative mixing in temperature (bottom) and O2 (top). Profiles were obtained at monitoring station located at lake center with a profiling CTD (YSI multiprobe) every 1 hour at 0.5 depth intervals.

S8

Figure S6. August 24 – 25, 2013 high-resolution water column temperature profiles over the campaign period obtained with CTD profiler deployed from the boat. Profile intervals were approximately 10 – 15 cm.

S9

0

Depth (m)

2

4

6

8 Aug 24 Afternoon Aug 24 Midnight Aug 25 Sunrise Aug 25 Noon

10 0.0

0.2

0.4

0.6

-1

CH4 (mol L )

Figure S7. Left: August 24 – 25, 2013 time series of CH4, CO2, O2 and temperature from probes mounted to the side of the boat. Hashed areas are times when boat was underway or in the harbor. Non-hashed areas are while boat was drifting during transects (transect number indicated at top of plot) towards the middle of the lake. Right: Corresponding CH4 profiles during the campaign.

S10

-4.6

Dissipation of TKE, Log10  (W kg-1)

-4.8 -5.0

Equation

y = a + b*x

Weight

No Weighting

Residual Sum of Squares

1.04933

Pearson's r

0.96829

Adj. R-Square

0.93678 Value

-5.2

K

Intercept Slope

Standard Error

-7.73306

0.06064

0.45024

0.01324

-5.4 -5.6 -5.8 -6.0 -6.2 -6.4 -6.6 3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

Wind speed w10m (m s-1) Figure S8. Log10 of dissipation (ε) rate of turbulent kinetic energy (TKE) in surface layer (1-2 meters) as a function of wind speed. Red dots were removed (first ~2 hours) from the correlation due to large divergence between the wind speed and turbulence as seen on Figure 1a. R2 with all data points is 0.65.

S11

4.5

-50

CH4 flux (FCH4) Linear Fit, R2 = 0.74 CO2 flux (FCO2)

3.5

-40

Linear Fit, R2 = 0.67 3.0 -30 2.5

2.0 -20 1.5

1.0

-10 -6.2

-6.0

-5.8

-5.6

-5.4

-5.2

-5.0

Log10 of Dissipation Rate of TKE (W kg-1)

Figure S9. Fluxes, FCH4 and FCO2 (top) as a function of the dissipation rate of turbulent kinetic energy (TKE).

S12

FCO2 (mmol m-2 d-1)

FCH4 (mmol m-2 d-1)

4.0