Ministry of Land, Infrastructure, Transport and Tourism

Hideaki SAITO

Director International Negotiations Office

Ocean Development and Environment Policy Division Maritime Bureau

Ministry of Land, Infrastructure, Transport and Tourism Japan

A. Reduce Activity level (transport volume) ⇒ Uncontrollable by the maritime industry,

but determined automatically by world economic growth.

B. Improve energy efficiency ⇒ Energy efficiency improvement can be achieved by

maritime sector’s efforts through the following measures.

B-1: Technical measures (improving hardware)

B-2: Operational measures (operating “wisely”)

Back to Basic: How to reduce GHG Emissions

IMO should focus on this.

IMO should not seek this way.

Emissions from the International Shipping Sector

0

10

20

30

year

Million CO2-ton 3,000

2,000

1,000 870

1,057

2,681 rise threefold

approx. equal to emissions from Germany

Source : Second IMO Greenhouse Gas study 2009

Emissions (g) = Activity (ton mile) x Energy Efficiency (g/ton mile)

In principle, volume of GHG emissions is

determined by two elements only, which are

“Activity” and “Energy Efficiency”.

1

Thus there are only two ways to reduce

emissions from shipping.

EEDI (Energy Efficiency Design Index)

< for New Ships > - Calculate Attained EEDI values - Meet Required EEDI values - Baseline will be lowered in a phased way

SEEMP (Ship Energy Efficiency Management Plan)

< for New & Existing Ships > - Develop a ship specific SEEMP

Technical Measures Operational Measures

1st Policy Package ⇒ amendments to the MARPOL Annex VI (Entry into force on 1 January 2013)

B. Improvement of Energy Efficiency B-1: Technical Measures B-2: Operational Measures

Components of Emissions Reductions

Snapshot on CO2 emissions regulations at the IMO

2

Operational Measures

Is there any room for further efforts ?

Discussion so far on Data Collection System

IMO/MEPC 62 (July 2011) adopted the amendments to MARPOL Annex VI on EEDI regulation for reducing GHG emissions from international shipping.

(Entry into force on 1st January 2013)

For further measures to improve the energy efficiency of ships, at MEPC 65 (May 2013), the US proposed a “Phased approach” for Data Collection System, and many countries including Europeans and Japan supported this approach.

The MEPC started to discuss this issue, in the first instance, on framework for data collection on the energy efficiency of ships.

Also Japan, the US, Germany and EMSA made suggestions on metrics for further improving energy efficiency.

At MEPC 66 (April 2014), IMO undertook intensive discussions on “Data Collection System”, and a Correspondence Group was established.

3

Japanese proposal

Annual Efficiency Ratio (AER) = [g-CO2 / ton-mile]

EEOI

In the adverse condition with low cargo loads, etc

Design stage In Operation

Ship specific value

EEDI e.g. 2.5 (g/ton mile)

j : the fuel type; FCj : the annual mass of consumed fuel j; CFj : the fuel mass to CO2 mass conversion factor for fuel j;

DWT : the deadweight; D : the annual distance sailed in nautical miles;

Where: Fuel consumption: 17,381 ton/year CF=3.114 Distance sailed: 81,984 mile/year DWT: 230,000

AER = = 2.87 (g-CO2/ton mile)

Same units: Could be compared ! 4

𝐹𝐶𝑗 × 𝐶𝐹𝑗𝑗

𝐷𝑊𝑇 × 𝐷

In the calm sea with high cargo loads, etc

Annual Efficiency Ratio (AER)

In the calm sea with high cargo loads, etc

In the adverse condition with low cargo loads, etc

17,381×106×3.114230,000×81,984

Example of calculation of the AER

Japan undertook a brief analysis, based on the real data voluntarily provided by Japanese fleet.

This analysis intends to seek whether Annual

Efficiency Ratio (AER) could be an appropriate metric to capture and enhance energy efficiency from international ships.

During the last Session, the suggestion was made by the Committee that a “test” on metrics would be warrant.

A metric which would be employed by the IMO at a later stage of the data collection, should be that could appropriate capture increasing or decreasing trends of energy efficiencies of individual ships.

Type of ship Number of ship

Oil tankers 8

Bulk carriers 25

Container carriers 28

Information of the ships which is used for analysis

5

Analysis on Annual Efficiency Ratio (AER) with real data (MEPC67/5/4)

Oil tankers Bulk carriers

R-Squared values • oil tankers : approximately 1.0 • bulk carriers : approximately 1.0 • container ships : approximately 0.7

The regression curves and AER values have strong interrelations each other.

Concept of AER could be an appropriate candidate as a metric for this initiative.

y = 700.9223 x-0.4410

R² = 0.9792

0

2

4

6

8

10

12

14

0 50,000 100,000 150,000 200,000 250,000 300,000 350,000

AER

[g-C

O2

/To

n-m

ile]

DWT

AER (crude oil tanker) Regression(AER)

DWT

AE

R [

kg-C

O2/

Ton-

mile

s]

AER Regression curve

y = 1,330.9248 x-0.5054

R² = 0.9658

0

2

4

6

8

10

12

14

16

18

20

0 50,000 100,000 150,000 200,000 250,000

AER

[g-C

O2

/To

n-m

ile]

DWT

AER (bulk carrier) Regression(AER)

DWT

AE

R [

kg-C

O2/

Ton-

mile

s]

AER Regression curve

y = 541.4506 x-0.3558

R² = 0.6797

0

5

10

15

20

25

30

35

40

0 20,000 40,000 60,000 80,000 100,000 120,000

AER

[g-C

O2

/To

n-m

ile]

DWT

AER Regression(AER)

AE

R [

kg-C

O2/

Ton-

mile

s]

DWT

AER Regression curve

6

Result 1: AER values calculated and the regression curves

Container ships

Result 2: Appropriateness of AER

Data of three parameters for oil tankers during 2009-2011 Degrees of changes from 2009 values for oil tankers

0

20000

40000

60000

80000

100000

120000

0

1

2

3

4

5

6

7

8

2009 2010 2011

AER

(g/t

on n

m) (

bar)

Tanker A （314,020(DWT)）

Tanker B（302,478(DWT)）

Tanker C（105,083(DWT)）

fuel

cons

umpt

ion

(ton

) (so

lied

line)

/d

ista

nce

saile

d (n

m)

(dot

ted

line)

year

AER

[kg

-CO

2/to

n-m

iles]

Fuel

con

sum

ptio

n [to

n]

Dis

tanc

e sa

iled

[nm

]

year

0

20

40

60

80

100

120

140

2009 2010 2011degr

ees o

f cha

nges

fro

m 2

009

valu

es o

f A

ER (g

/ton

nm

) (ba

r)

/ fu

el c

onsu

mpt

ion

(ton

) (so

lied

line)

/dis

tanc

e sa

iled

(nm

) (d

otte

d lin

e) …

Tanker A （314,020(DWT)）

Tanker B（302,478(DWT)）

Tanker C（105,083(DWT)）

yearyear Fuel consumption

Distance sailed Fuel consumption Distance sailed

AER AER

Tanker B consumed larger fuels than Tanker C. But... Tanker B achieved a longer distance, carried larger cargoes than Tanker C. Calculated AER value of Tanker B shows a better efficiency ratio than that

of Tanker C.

AER is that could appropriate capture energy efficiencies of individual existing ships, taking well into account “transport work”. 7

Perc

enta

ge [%

]

Result 3: Importance of Transport work

0

20000

40000

60000

80000

100000

120000

140000

0

2

4

6

8

10

12

14

16

2009 2010 2011

AER

(g/t

on n

m) (

bar)

Container ship A（99,214(DWT)）

Container ship B（90,630(DWT)）

Container ship C（80,282(DWT)）

fuel

cons

umpt

ion

(ton

) (so

lied

line)

/d

ista

nce

saile

d (n

m)

(dot

ted

line)

year

0

20

40

60

80

100

120

140

2009 2010 2011degr

ees o

f cha

nges

fro

m 2

009

valu

es o

f A

ER (g

/ton

nm

) (ba

r)

/ fu

el c

onsu

mpt

ion

(ton

) (so

lied

line)

/dis

tanc

e sa

iled

(nm

) (d

otte

d lin

e)

Container ship A（99,214(DWT)）

Container ship B（90,630(DWT)）

Container ship C（80,282(DWT)）

year

AER

[kg

-CO

2/to

n-m

iles]

Fuel

con

sum

ptio

n [to

n]

Dis

tanc

e sa

iled

[nm

]

year year Data of three parameters for container ships

during 2009-2011 Degrees of changes from 2009 values for

container ships

AER

Distance sailed

Fuel consumption

Distance sailed

AER

Fuel consumption is increased

It would not be appropriate to rely on the fuel consumption figures for the data collection system. 8

Perc

enta

ge [%

]

The data of Ship B for fuel consumptions indicate the decrease in 2009-2010 and then the increase in 2010-2011.

The data for the distances of Ship B indicate a decreasing trend to a smaller extent in 2009-2010 and then the increasing trend to a larger extent in 2010-2011.

The calculated AER values for Ship B show the constant decrease (namely, the constant improvement of energy efficiency) during 2009-2011.

Establish efficiency metric and baselines

Discussion items - Mandatory or voluntary (necessity of amendments to MARPOL Annex VI)

- Scope of application (ship type, 400GT / 5,000GT, etc.)

- Range of data to be collected - Data collection and reporting process (frequency of measurement, treatment of ballast condition, data format, etc.)

- Means of enforcement, if it is mandatory, etc.

IMO

Ship

Centralized database • data collection and

analysis • Provide Annual report

Flag State or RO • Data collection • Submit an annual report

to the Flag State/RO and IMO

• Keep Certificate on board

• Verification of collected data

• Issue Certificate of compliance

• Submit data to IMO, etc.

Port State • Port State Control

(Check the Certificate)

• Establish the framework for data collection (fuel consumption, distance sailed, hours of service, DWT, etc) from each ship

Data Collection and Analysis

Data Collection and Analysis Phase (Phase 1) Pilot Phase (Phase 2)

Full Implementation Phase (Phase 3)

“Test run” to check an efficiency metric and a baseline selected

• Full Enforcement

• Further consider flexible measures or MBM

Details have not been discussed

Based on data collected during the Phase 1 period, consider an appropriate efficiency metric, and establish efficiency baselines.

[g/mile]

[g/ton mile] Distance sailed × DWT Fuel Consumption × Carbon Factor (CF)

The US : Yearly average of [J/hours] service hour Energy [joule]

EMSA : Yearly average of distance sailed

fuel consumption × Carbon factor (CF)

Japan : Yearly average of

Germany : annual Fuel Consumption [ton]

9

A way forward at IMO on Data Collection System to enhance energy efficiency of international shipping

Conclusion

1. The IMO GHG study indicates the strong growth of CO2 emissions from international shipping, and therefore, the IMO should focus on the energy efficiency improvement of individual ships, but not on capping CO2 emissions in absolute terms.

2. EEDI & SEEMP regulation is a big step forward. But this is not enough and there is a room for all the existing ship to make further efforts.

3. Therefore, the IMO/MEPC should make efforts to establish a Data Collection system.

4. Japanese proposal for a metric, i.e., Annual Efficiency Ratio (AER), has the following characteristics;

(1) aims at improving energy efficiency of individual ships;

(2) the same unit with EEDI is employed based on DWT;

(3) strong correlation and robustness are found;

(4) appropriately takes into account “transport work”; and,

(5) only three data (fuel consumption, distance sailed and DWT) are required, and these have been already subject to other mandatory instruments.

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Thank you very much for your interests, and any questions?

Contact: Hideaki SAITO Director International Negotiations Office Ocean Development and Environment Policy Division Maritime Bureau MLIT, JAPAN saito-h55rp@mlit.go.jp

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