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Effects of Vertical DIC Distribution on Storage

Efficiencies of Direct Injection of CO2 into the Ocean

Baixin Chen, M. Nishio, and M. Akai

National Institute of Advanced Industrial Science and Technology (AIST), 1-2-1 Namiki, Tsukuba East, Tsukuba 305-8564, Japan

ARCS project, founded by MITE, JapanARCS

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Why ocean sequestration? (Marchetti, C. Climate Change 1977, 1, 59.)

Large capacity (IPCC Srpt. on CCS 05) :

“Roughly 2,300 to 10,700 GtCO2 would be added to the ocean (above the natural pre-industrial background) in equilibrium with atmospheric CO2 stabilization concentrations ranging from 350 ppm to 1000 ppm, regardless of whether the CO2 is initially released to the ocean or the atmosphere.”

Actually, it is an artificially acceleration of natural oceanic uptaking of CO2 across air/sea interface (IPCC Srpt. On CCS 05)

Over the past 200 years the oceans have taken up 500 GtCO2 from the atmosphere out of 1300 GtCO2 total anthropogenic emissions. .

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Questions:Assessments on CO2 Ocean Sequestrations

How long it could be kept in the ocean ? (efficiency) OGCMs (depth, locations) (Caldeira et al. in GRL, JGR 02; Orr et

al. in Climate Change 02 and GHGT-5-00; …..) Box models (depth, bio-chemical systems) (Sohma et al, JGR-05;

Herzog et al. Climatic Change, 03 ….)

How about the injection parameters?

Is it safe for marine bio-masses? (bio-impacts) Lab. Exps. (Acute injury of fishes, Mortality and Injury of zooplankton

by Portner; Shirayama; Ishimatsu; JO and IPCC SRPT. on CCS) for Near-field and short-terms.

Long-term impacts on bio-eco system ( ? )

Do the Injection parameters play the role ?

The impacts on global ecosystem ( ? )

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How to perform (IPCC Srpt. on CCS, 2005)

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Injection of CO2 by moving-ships

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CO2 Injection Nozzle & Droplet Size Distribution (Minamiura et al., GHGT-7, 2004)

CO2 drops from Lab. Exp.

Drop deformation

Hydrate layer formed at the interface

Nozzle

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0 5 10 15 20 25 0

5

10

15

20

CO2 Droplets Diameter (mm)

O: P=10.1MPa;T=275K O: P=15.1MPa;T=278K O: P=20.1MPa;T=278K

Exp Data (Ozaki et al)

: Cdr Rigid spheres Eq. (2)

:Cdd Rigid spheres with deformation Eq.(1) Ter

min

al v

eloc

ity

of C

O2

drop

let

(cm

s-1

)

Sub-models of drag coefficient (Lab. data from Dr. Ozaki)

Re10)Re104596.1

Re103484.86419.5(0.1)A/A(

)2(Re/)Re125.01(24Cd

)1()A/A(CdCd

426

3Cdeqeff

72.0r

Cdeqeffrd

1.0 1.5 2.0 2.5 3.0 3.5 0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

O: P=10.1MPa;T=275K O: P=15.1MPa;T=278K O: P=20.1MPa;T=278K Exp data (Ozaki et al)

: Cdr Rigid spheres Eq. (2) : Cdd Rigid spheres with deformation Eq.(1)

Logarithmic Reynolds Number

Dra

g C

oeff

icie

nt C

dr a

nd C

d d

Re

w

rDuRe

ur =|ud – uw|

The relative velocity

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How to handle the injection parameters ?

1. Plume dynamics (coupling the injection parameters and currents) in short-term

2. For long-term efficiency,

By OGCMs for long-term Using fine resolution:

10th meters vertically

(Very difficult if not impossible currently) Nesting grids systems

Good and will be trying

By Box models OK (How about the horizontal transportation roles?)

In this study :

Implemented the initial vertical distribution of DIC from (1) to the existed data from (2).

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: the storage efficiency with an initial vertical distribution (pdf)

: the storage efficiency without initial vertical distributions (from OGCM data).

h : the depth of the ocean (m)

t : time (year)

P[x(h)] : the initial mass pdf of DIC in vertical distribution

as a normalized depth (x (h)).

Effect of injection parameters on storage efficiency:

1

0 0 )]([),()( dxhxPtht CC

)(tC

),(0 thC

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Long-term storage efficiency data

interpolated from OGCMs

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The data can be interpolated numerically (Caldeira et al. GRL 2002)

Injection site: Tokyo T > 100 years

T < 100 years

T = 20 - 100 yrs

T = 120 - 500 yrs

Injection site: Tokyo

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Initial Vertical Distributions of DIC

produced by coupling injection parameters with ocean current

from two-phase models

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Near-field Two-phase Model

CO2 droplet Dynamics and biological impacts

X1

X2

X3

Ocean surface

Can go to the bottom

Turbulent diffusion

Injection ports installed nozzles

Towing pipeInitial DIC distribution

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Model validation (Chen et al., JGR, 05)

(vs field Exp data by P. Brewer et al. 2002)

0.00

0.20

0.40

0.60

0.80

1.00

10 25 40 55 70

Elapsed Time (min)

Dro

plet

Dia

met

er (

cm)

Modeling Prediction (Droplet A)

Modeling Prediction (Droplet B)

:Observation Data of Droplet A (P. Brewer et al)

:Observation Data of Droplet B (P. Brewer et al)

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O u t l i n e o f C O 2 D r o p l e t P l u m e

C O 2 R i c h - w a t e r P l u m e

1 . 3 4 1 . 2 6 1 . 1 7 0 . 8 9 0 . 6 5 0 . 0 0

Evolution of DIC Plumes (Chen et al., JGR, 05)

T=1.0 min T=23 min T=70 min

X=180 mX=10 m X=10 m X=10 m

Injection rate : 100 kg/sec

Initial drop size: 15 mm

Injection depth : 2000 m

Injection port : Horizontal

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Vertical distributions of DIC

Injection site: Tokyo at Depth of 2000 m

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Effect of initial DIC vertical distribution on

efficiency

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CO2 Injection Parameters

Injection type: Moving-ship

Injection rate: 100kg/sec by moving-ship (0.1 Ggt C /year)

Droplet sizes: 5, 10, 15, 20, 30, 40 mm

Injection depth: 1000, 1500, 2000, 2500 m

Injection site: Near Tokyo (T, S and current data )

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Injection site: Tokyo

Effects of initial droplet size on efficiency

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Effects of injection parameters on efficiencies

Injection site: Tokyo

Time : 500 yrscocS 0.1

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Efficiency and (Sensitivity)

Injection depth H (m)

800 1500 2000 3000

By 8 OGCMs(Orr et al. GHGT-5)

15 – 37

(+0.42)

26 – 57

(+0.35)

50 – 82

(+0.25)

By 8 sites (MOM)(Tokyo, New York, Bombay …, By Caldeira et al. GRL 2002)

15 – 30

(+0.33)

40 – 57

(+0.17)

70 – 89

(+0.10)

By droplet sizes

(D0 = 5 – 40 mm)20 – 25

(0.21)*

38 – 47

(0.20)

50 – 60

(0.11)

62 – 72

(0.10)**

* : H = 1000 m and D0 = 5 – 10 mm; ** : H = 2500 m

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Conclusions & discussions

Within 500 years after releasing CO2 at rate of 0.1 Ggt C /year by moving-ship:

Efficiency is related with not only depths and sits, but also drop size injected.

For droplets size D0 = 5 – 40 mm, the storage efficiencies could be reduced by range of 5% to 20% if release depth less than 2600m due to the rising plumes.

Implement of DIC vertical pdf into OGCMs for further checking. (Nesting grids system ?)

The roles of injection parameters on biological impacts in near-field should is another challenge.

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Thank you !

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How long the CO2 injected could be kept in the ocean ?

Efficiency or retention : OGCMs (depth, locations)

Caldeira et al. (GRL, JGR , 02)

Orr et al. (Climate Change 02 and GHGT-5-00 )

…..

Box models (depth, bio-chemical systems)

Herzog et al. (Climatic Change, 2003)

Sohma et al, (JGR, 20050)

….

In this study :

If the injection parameters play the role on storage efficacy?

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Methodologies:

Implement the near-filed two-phase box model to the OGCM by:

Provide the initial vertical distributions of DIC from near-filed model

Use data of long-term storage efficiency from OGCMs and Box models to estimate the effects of initial-vertical DIC distribution.

because the time scales :

dtOGCM (2 ~ 3 hrs) > Tdiss (1~ 1.5 hrs)

We checked the injection depths and D0s for two injection types (horizontal and vertical injection ports) at a fixed injection rate (100kg/sec).

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Ascending /Descending of CO2 droplet in the ocean

-800

-600

-400

-200

0

200

400

600

800

0 3 6 9 12 15 18 21 24

Initial Diameter of CO2 Droplet (mm)

Asc

endi

ng /d

esce

ndin

g D

ista

nces

(m

) Release depth: 1000m

Release depth: 2000m

Release depth: 2895m

Release depth: 2900m

Release depth: 3000m

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Model of an Individual CO2 Droplet (dissolution and movement)

dt

)mln(du)C

D

ug).((

dt

du crd

r

s

c

c

sr

4

301

2

)D

CDSh2

dt

d

3

D(

1

dt

dD sfc

c

Key Parameters:

•Sh : Sherwood number

•Cs: The solubility

•α : The effective area coefficient

•Cd: Drag coefficient