Paradox of international maritime organization's carbon intensity indicator

Abstract

The 76th session of the Marine Environment Committee (MEPC 76) of the International Maritime Organization adopted several mandatory measures in June 2021 to reduce carbon emissions from ships. One of the measures is the carbon intensity indicator (CII), which is the carbon emissions per unit transport work for each ship. Several options of CIIs are available and none of them is chosen to be applied yet. We prove that, at least in theory, requiring the attained annual CII of a ship to be less than a reference value, no matter which CII option is applied, may increase its carbon emissions. Therefore, more elaborate models, combined with real data, should be developed to analyze the effectiveness of each CII option and possibly to design a new CII.

Full text

Paradox of international maritime organization's carbon intensity indicator
Shuaian Wang
a
, Harilaos N. Psaraftis
b
, Jingwen Qi
a
,
*
a
Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region
b
Department of Technology, Management and Economics, Technical University of Denmark, Denmark
ARTICLE INFO
Keywords:
Maritime transportation
Carbon dioxide emission
International maritime organization (IMO)
Global regulation
ABSTRACT
The 76th session of the Marine Environment Committee (MEPC 76) of the International Maritime Organization
adopted several mandatory measures in June 2021 to reduce carbon emissions from ships. One of the measures is
the carbon intensity indicator (CII), which is the carbon emissions per unit transport work for each ship. Several
options of CIIs are available and none of them is chosen to be applied yet. We prove that, at least in theory,
requiring the attained annual CII of a ship to be less than a reference value, no matter which CII option is applied,
may increase its carbon emissions. Therefore, more elaborate models, combined with real data, should be
developed to analyze the effectiveness of each CII option and possibly to design a new CII.
1. Introduction
Maritime decarbonization has become a priority area for policy-
makers. The International Maritime Organization (IMO), which is the
United Nations body for international shipping, adopted an initial
strategy on the reduction of greenhouse gas emissions from ships in 2018
(IMO, 2018). The Initial IMO Strategy sets up to reduce carbon dioxide
(CO
2
) emissions per transport work by at least 40% by 2030 compared to
2008, and to reduce the total annual greenhouse gas (GHG) emissions
from international shipping by at least 50% by 2050 compared to 2008.
The 76th session of the Marine Environment Committee (MEPC 76) of
the IMO adopted several mandatory measures in June 2021 to reduce
carbon emissions from ships, which will contribute to achieving the
carbon emission targets set by the Initial IMO Strategy (IMO, 2021a). One
of the measures is the carbon intensity indicator (CII), which measures
the carbon emissions per unit transport work for each particular ship.
Comparing the CII value of a ship over a year with the reference CII
values
1
determined by the IMO, the performance of the ship will be rated
as ‘A’(major superior), ‘B’(minor superior), ‘C’(moderate), ‘D’(minor
inferior), or ‘E’(inferior). A rating of ‘A’,‘B’,or‘C’is required for
compliance, and corrective actions should be taken for ships receiving ‘D’
for three consecutive years or ‘E’for one year. Ship owners should thus
try to achieve a rating of ‘C’or above for their ships. The reference CII
values will decrease with time. MEPC 76 decided for each ship to achieve
an annual reduction of 1% until 2023 and 2% from 2023 to 2026, leaving
open the required reductions until 2030. Note that 2030 is the year of the
intermediate target, which stipulates a reduction of CII of at least 40% in
2030 versus the 2008 level.
Supply based CII:CIIsupply ¼Annual carbon emissions of the ship ðgÞ
The ship’s deadweight tonnage times the sailing distance in the year (1)
* Corresponding author.
E-mail addresses: wangshuaian@gmail.com (S. Wang), hnpsar@dtu.dk (H.N. Psaraftis), jingwen.qi@connect.polyu.hk (J. Qi).
1
The reference CII values are expected to depend on factors such as ship type and size.
Contents lists available at ScienceDirect
Communications in Transportation Research
journal homepage: www.journals.elsevier.com/communications-in-transportation-research
https://doi.org/10.1016/j.commtr.2021.100005
Received 22 July 2021; Received in revised form 26 August 2021; Accepted 26 August 2021
Available online xxxx
2772-4247/©2021 The Author(s). Published by Elsevier Ltd on behalf of Tsinghua University Press. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Communications in Transportation Research 1 (2021) 100005

According to the Fourth IMO GHG Study carried out by the IMO
(2020), there are at least four potential versions of CII, defined as follows:
Demand
based CII:CIIdemand ¼Annual carbon emissions of the ship ðgÞ
Actual tonne miles carried by the ship in the year
(2)
Distance
based CII:CIIdistance ¼Annual carbon emissions of the ship ðkgÞ
Actual sailing distance of the ship in the year
(3)
Sailing time
based CII:CIIsailing time ¼Annual carbon emissions of the ship ðtonneÞ
Actual sailing time of the ship in the year
(4)
The units of the four versions of CII are: g/dwt/nm
2
for supply-based
CII, g/tonne/nm for demand-based CII, kg/nm for distance-based CII,
tonne/h for sailing time-based CII (IMO, 2020). The IMO/MEPC 76 has
not yet agreed on which version to use, but all are on the table (IMO,
2021b). Despite the intention of CII to reduce carbon emissions, the
Baltic and International Maritime Council (BIMCO) has warned that the
carbon emissions may increase due to the application of CII (Osler,
2021). In this paper, we prove that paradoxes can occur no matter which
CII is used, that is, adopting the CII measure will increase carbon emis-
sions in some situations. Combined use of different CII may also increase
carbon emissions in some situations.
2. Literature review
A rule/decision does not always achieve its intended aim because the
target people (the followers) may abide by the rule/react to the decision
in a way different from what the rule/decision maker (the leader) an-
ticipates. The Stackelberg game theory, which analyzes the interaction
between a leader (e.g., government) and one or multiple followers (e.g.,
industry), best explains this phenomenon. In such a game, the leader
makes the decision first and then the followers make decisions in view of
the leader's decision. We review a few examples in maritime trans-
portation and road transportation in which the actual outcome is oppo-
site to the leader's intended aim.
In maritime transportation, Cariou and Cheaitou (2012) examined
the effectiveness of an assumed upper speed limit zone of the European
Union (EU) water. Since ships burn less fuel per nautical mile when
sailing at lower speeds, the intended aim of enforcing an upper speed
limit is to reduce the fuel consumption of ships and thereby to reduce the
CO
2
emissions. Cariou and Cheaitou (2012) revealed that ships will slow
down within the upper speed limit zone and speed up outside the zone.
Because the fuel consumption per nautical mile is a convex increasing
function of speed, different speeds within and outside the zone will
generate more CO
2
emissions than the amount when ships sail at constant
speeds without an upper speed limit zone. Similar paradoxes have been
considered in a series of related papers. For example, Zhuge and Wang
et al. (2020) investigated the subsidy design problem in a vessel speed
reduction incentive program under government policies, considering the
extra ship emissions incurred. In the paper, given the subsides, shipping
lines may choose to reduce the sailing speed in the vessel speed reduction
zone and contribute to the reduction of ship emissions in the area.
However, some new ships attracted by the program will cause extra
emissions.
In land transportation, the most well-known paradox is the Braess
Paradox, which offers an example in which constructing a new road
makes every private driver experience a longer travel time (Braess,
1968). In a two-mode transport system consisting of public transit ser-
vices and a highway for private drivers, Downs (1962) and Thomson
(1977) showed that the expansion of the highway may decrease the
travel utility of all the travelers (both public transit users and private
drivers). The rationale of the Downs–Thomson Paradox is that the
expanded highway will attract some public transit users to become pri-
vate drivers; then the transit authority may reduce the public transit
service frequency in view of the reduced number of public transit service
users. The reduction in frequency will shift more public transit service
users to the highway, leading to a vicious circle. In the end, travelers of
both modes may suffer from the highway expansion. To date, such
paradox is still an important factor considered in optimization problems
in land transportation (Schadschneider and Bittihn, 2020;Bittihn and
Schadschneider, 2021;Huang and Chen et al., 2021).
Our research complements the existing literature of paradoxes in
transportation management and sheds insights into shipping emission
management.
3. Paradox of existing possible CII
3.1. Paradox of the supply-based CII
We use an example to show the paradox of the supply-based CII.
Example 1 (A ship sails empty to comply with the supply-based
CII measure): A ship owner has a bulk cargo ship with a deadweight
tonnage of Q¼80;000 tonnes; we assume that the weights of fuel,
ballast water, provisions, and crew make up a small proportion of Qand
can thus be ignored. For simplicity, in our example we assume that the
ship sails at a fixed speed v¼13 knots. The fuel consumption rate of the
ship, denoted by fðwÞ(tonne/nm), is a monotonically increasing function
of the cargo payload w(tonne). For this ship fðQÞ¼0:1095 tonne/nm,
fð0Þ¼0:8fðQÞtonne/nm. We also assume that the fuel cost is the
dominant component of the total operational costs for the ship owner.
The fuel used is heavy fuel oil (HFO) and burning one tonne of HFO will
generate
α
¼3:114 tonnes of carbon dioxide (CO
2
). The ship owner has
to transport cargo of payload equal to Q(tonnes) over a distance of L¼
2;766 nm, between Jakarta, Indonesia, and Qingdao, China, each year.
The ship completes N¼20 voyages each year. No ballast voyages will be
involved.
In 2023, the total amount of carbon emissions will be 106N
α
fðQÞL(g)
and the attained annual operational supply-based CII for the ship in the
year will be 106
α
fðQÞ
Q¼4:26 g/tonne/nm. According to the tentative rule
of the IMO, in 2023, a bulk carrier with a deadweight tonnage less than
279,000 tonnes will be rated as ‘C’if its attained annual operational
supply-based CII is between 3.78 and 4.26 g/tonne/nm (ClassNK, 2021).
Therefore, the ship will receive a ‘C’rating in 2023.
In 2024, to receive a ‘C’rating, attained annual operational supply-
based CII must be between 3.70 and 4.17 g/tonne/nm (ClassNK,
2021). Therefore, to achieve a rating of ‘C’, after transporting the cargo to
the destination, the ship owner has to sail the empty ship over a distance
of l1¼335:8 nm (maybe sail for l1=2 away from the destination port and
then return to it), and the actual supply-based CII for the ship will be
106ð
α
fðQÞLþ
α
fð0Þl1Þ
QðLþl1Þ¼4:17, meeting the requirement of a ‘C’rating. As a
result, the amount of carbon emissions will increase by N
α
fð0Þl1¼1;832
tonnes.
In Example 1, the ship sails empty to reduce the carbon intensity,
which actually increases the carbon emissions. We can also design ex-
amples to show that in some situations two ships may be used to meet the
supply-based CII requirement while one ship is enough to fulfill the
transport work, and produce unnecessary carbon emissions.
2
The dwt is the acronym for deadweight tonnage; nm is the acronym for
nautical mile (1 nautical mile ¼1.852 km).
S. Wang et al. Communications in Transportation Research 1 (2021) 100005
2

3.2. Paradox of the demand-based CII
We use an example to show the paradox of the demand-based CII.
Example 2 (A ship sails full over a longer distance than necessary
to comply with the demand-based CII measure): The basic setting is
the same as that of Example 1, but the cargo trade is imbalanced and the
ship has to sail back empty. It completes M ¼10 laden voyages and
M¼10 ballast voyages each year.
In 2023, the total amount of carbon emissions is 106Mðaf ðQÞLþ
af ð0ÞLÞðgÞ. The attained annual operational demand-based CII for the
ship will be 106ðaf ðQÞþaf ð0ÞÞ
QSuppose that in 2023, the upper bound of the
attained annual operational demand-based CII for a ‘C’rating is equal to
106ðaf ðQÞþaf ð0ÞÞ
Q, that is, the ship will receive a ‘C’rating in2023.
3
Suppose that in 2024, the upper bound of the attained annual oper-
ational demand-based CII for a ‘C’rating is equal to 0:98 106ðaf ðQÞþaf ð0ÞÞ
Q.
To achieve a rating of ‘C’, instead of transporting the cargo over a dis-
tance of L, the ship owner has to intentionally detour
4
for a distance of
l2¼ðfðQÞþfð0ÞÞL
49fð0ÞfðQÞ, and the actual demand-based CII for the ship will be
106½
α
fðQÞðLþl2Þþ
α
fð0ÞL
QðLþl2Þ¼0:98 106ð
α
fðQÞþ
α
fð0ÞÞ
Q. Evidently, the amount of car-
bon emissions will increase by M
α
fðQÞl2¼M
α
fðQÞðfðQÞþfð0ÞÞL
49fð0ÞfðQÞ(tonne).
In Example 2, instead of sailing empty back, the ship may try to secure
some cargo when sailing back so that it does not have to detour on the
laden leg, and the freight rate of the back-haul cargo can be truly negative
if the extra fuel consumption for carrying the back-haul cargo is less than
the extra fuel consumption during detour on the laden leg.
3.3. Paradox of the distance-based CII
We use an example to show the paradox of the distance-based CII.
Example 3 (A ship sails empty to comply with the distance-based CII
measure): The basic setting is the same as that of Example 1.
In 2023, the total carbon emissions equal 103N
α
fðQÞL(kg), and the
attained annual operational distance-based CII for the ship will be
103
α
fðQÞ. Suppose that in 2023, the upper bound of the attained annual
operational distance-based CII for a ‘C’rating is equal to 103
α
fðQÞ, that
is, the ship will receive a ‘C’rating in 2023.
Suppose that in 2024, the upper bound of the attained annual oper-
ational distance-based CII for a ‘C’rating is equal to 0:98 103
α
fðQÞ.To
achieve a rating of ‘C’, besides transporting the cargo over a distance of L
in each voyage, the ship owner has to sail empty for a distance of l3¼
fðQÞL
49fðQÞ50fð0Þ. Then the actual distance-based CII for the ship will be
103ðN
α
fðQÞLþN
α
fð0Þl3Þ
NðLþl3Þ¼0:98 103
α
fðQÞ. Evidently, the amount of carbon
emissions will increase by N
α
fð0Þl3¼N
α
fð0ÞfðQÞL
49fðQÞ50fð0Þ(tonne).
In Example 3, the ship sails empty for an extra distance to reduce the
carbon intensity, which actually increases the carbon emissions.
3.4. Paradox of the sailing time-based CII
We use an example to show the paradox of the sailing time-based CII.
Example 4 (A ship sails empty to comply with the sailing time-based
CII measure): The basic setting is the same as that of Example 1.
In 2023, the total carbon emissions equal N
α
fðQÞL(tonne), and the
attained annual operational distance-based CII for the ship will
be
α
vf ðQÞ. Suppose that in 2023, the upper bound of the attained annual
operational sailing time-based CII for a ‘C’rating is equal to
α
vf ðQÞ, that
is, the ship will receive a ‘C’rating in 2023.
Suppose that in 2024, the upper bound of the attained annual oper-
ational sailing time-based CII for a ‘C’rating is equal to 0:98
α
vf ðQÞ.To
achieve a rating of ‘C’, besides transporting the cargo over a distance of L
in each voyage, the ship owner has to sail empty for a distance of l4¼
fðQÞL
49fðQÞ50fð0Þ. Then the actual sailing time-based CII for the ship will be
α
vðNf ðQÞLþNfð0Þl4Þ
NðLþl4Þ¼0:98
α
vf ðQÞ. Evidently, the amount of carbon emissions
will increase by N
α
fð0Þl4¼N
α
fð0ÞfðQÞL
49fðQÞ50fð0Þ(tonne).
In Example 4, the ship sails empty for an extra distance to reduce the
carbon intensity, which actually increases the carbon emissions.
In this section, we have discussed the paradox of four existing CII, and
the paradox of combinations of these CIIs will be displayed in Section 4.
4. Paradox of combined CII
4.1. Paradox of weighted sum of existing CII
A weighted sum of the aforementioned forms of CIIs can be used as a
new form. We consider the case in which all the four CIIs have the same
weight as an example, and the weighted sum is defined as follows:
Weighted sum CII:CIIweighted sum ¼0:25
CIIsupply þCIIdemand þCIIdistance þCIIsailing time:(5)
We use an example to show the paradox of the weighted sum CII in
Eq. (5).
Example 5 (A ship sails empty to comply with the weighted sum
CII): The basic setting is the same as that of Example 1. In this section,
due to the complexity of Eq. (5), we will prove that the ship can obtain a
lower weighted sum CII by sailing empty, and the total carbon emissions
will increase.
In 2023, the total carbon emissions equal N
α
fðQÞL(tonne), and the
attained annual operational weighted sum CII for the ship will
be
α
fðQÞ2106þ103QþQv
4Q(¼0:25106
α
fðQÞ
Qþ106
α
fðQÞ
Qþ103
α
fðQÞþ
α
vf ðQÞ).
Suppose that in 2023, the upper bound of the attained annual operational
weighted sum of CII for a ‘C’rating is equal to
α
fðQÞ2106þ103QþQv
4Q, that is,
the ship will receive a ‘C’rating in 2023.
Suppose that in 2024, the upper bound of the attained annual oper-
ational weighted sum CII for a ‘C’rating equals
α
4ðfðQÞLþfð0Þl5Þ106þ103QþvQ
QðLþl5Þþ106
LQ (¼0:25106
α
ðfðQÞLþfð0Þl5Þ
ðLþl5ÞQþ
106
α
ðfðQÞLþfð0Þl5Þ
LQ þ103
α
ðfðQÞLþfð0Þl5Þ
Lþl5þ
α
vðfðQÞLþfð0Þl5Þ
Lþl5), which can be achieved
by sailing empty for a distance of l5in each voyage. By comparing these
two weighted sums, we obtain the following equation:
α
fðQÞ2106þ103QþQv
4Q
α
4ðfðQÞLþfð0Þl5Þ106þ103QþvQ
QðLþl5Þþ106
LQ
¼
α
l5
Q106þ103QþQv
Lþl5fðQÞ106þ103QþQv
Lþl5
þ1
Lfð0Þ:(6)
In the basic setting of Example 1, we assume that fð0Þ¼0:8fðQÞ, and
therefore the right-hand side of Eq. (6) can be rewritten as
α
l5
QfðQÞ0:2106þ103QþQv
Lþl50:81
L, which will be positive when
l5<L
4ð106þ103QþQv 4Þ. In that case, the upper bound for a ‘C’
rating in 2024 is lower than that in 2023.
In conclusion, in Example 5, the ship sails empty to meet the rating
requirement, which actually increases the carbon emissions.
3
The IMO has not yet published any guideline on the required annual oper-
ational demand-based CII and hence the required annual operational demand-
based CII values for 2023 and 2024 in Example 2 are assumed.
4
Transporting less cargo is also an option. The ship owner will choose the
option (transport less cargo or detour) with a higher profit. In Example 2 we
assume detour is preferable.
S. Wang et al. Communications in Transportation Research 1 (2021) 100005
3

4.2. Paradox of meeting at least one existing CII
Another combined form of CII is to regulate that the ship should have
the ‘C’rating in at least one of the four existing CIIs. We use an example to
show the paradox of this regulation on CII.
Example 6 (A ship sails empty or full over a longer distance than
necessary to comply with this regulation on CII): The basic setting is
the same as that of Example 1. Suppose that in 2023, the ship will obtain
a rating of ‘C’or above in at least one of the CIIs. Then in 2024, due to the
decline of the upper bounds of the attained annual operational CIIs, the
ship will fail to obtain a rating of ‘C’or above in any of the CIIs.
Considering the operating cost, the ship is likely to make operational
amendments to obtain a ‘C’rating in one of the CIIs to abide by the
regulation. If the ship operator decides to lower its annual operational
supply-based CII, distance-based CII, or sailing speed-based CII by sailing
empty for a longer distance than necessary, the total carbon emissions
will increase according to Examples 1, 3, and 4. If the ship operator de-
cides to lower its annual operational demand-based CII by sailing full for
a longer distance than necessary, the total carbon emissions will increase
according to Example 2.
In conclusion, in Example 6, the amendments adopted by the ship to
reduce the carbon intensity will actually increase the total carbon
emissions.
4.3. Paradox of meeting multiple existing CII simultaneosly
On top of Example 6, consider a more strigent regulation that stipu-
lates ships should obtain ‘C’rating or above in at least 2 CIIs. We use an
example to show the paradox of this regulation on CII.
Example 7 (A ship sails empty over a longer distance than
necessary to comply with this regulation on CII): The basic setting is
the same as that of Example 1. Suppose that in 2023, the ship will obtain
a rating of ‘C’or above in distance-based CII and sailing time-based CII,
and ‘D’or ‘E’in the other CIIs. Then in 2024, due to the decline of the
upper bounds of the attained annual operational CIIs, the ship will fail to
obtain a rating of ‘C’or above in any of the CIIs. Considering the oper-
ating cost, the ship is likely to make operational amendments to obtain a
‘C’rating in two of the CIIs to abide by the regulation. Suppose that the
ship needs to sail empty for at least ls,ld, and ltto obtain a ‘C’rating in
supply-based CII, distance-based CII, and sailing time-based CII, respec-
tively. And we have ls>ld>lt. Then the ship operator will choose to sail
empty for ldto obtain a ‘C’rating in distance-based CII and sailing time-
based CII. As a result, the total carbon emissions will increase according
to Examples 3 and 4.
In conclusion, in Example 7, the amendments adopted by the ship to
reduce the carbon intensity will actually increase the total carbon
emissions.
5. Concluding remarks
The seven simple examples described above prove the paradox that,
at least in theory, the CII requirement may increase carbon emissions of
some ships in some situations. More elaborate models, combined with
real data, can and should be developed to analyze, for each CII option, the
proportion of ships whose carbon emission will increase, the average
amount of increase for these ships, and the average amount of decrease
for the other ships. The design of indicators to achieve utmost carbon
emissions reduction, for example, a function of the four existing CII
metrics, or requiring the average carbon intensity of ships owned by a
company to comply with the CII rather than each individual ship
5
, is also
worth exploring.
Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Acknowledgements
This research is supported by the National Natural Science Founda-
tion of China (Grant Nos. 72071173 and 71831008).
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Shuaian (Hans) Wang is a Professor at The Hong Kong Poly-
technic University (PolyU). His research interests include ship-
ping operations management, green shipping, big data in
shipping, port planning and operations, urban transport
network modeling, and logistics and supply chain management.
He dedicates to rethinking and proposing innovative solutions
to improve the efficiency of maritime and urban transportation
systems, to promote environmentally friendly and sustainable
practices, and to transform business and engineering education.
5
This option was proposed by Denmark to the IMO (Adamopoulos, 2021) but
did not receive support at MEPC 76.
S. Wang et al. Communications in Transportation Research 1 (2021) 100005
4

Harilaos N. Psaraftis is a Professor at the Technical University of
Denmark (DTU), Department of Technology, Management and
Economics. He has a diploma from the National Technical
University of Athens (NTUA) (1974), and two M.Sc. degrees
(1977) and a Ph.D. (1979) from MIT, USA. He has been Assis-
tant and Associate Professor at MIT from 1979 to 1989 and
Professor at NTUA from 1989 to 2013. He has participated in 20
or so EU projects, and has coordinated 3 of them, including
project SuperGreen on European green corridors (2010–2013).
He has been a member and chairman of various groups at the
IMO, and has also served as CEO of the Piraeus Port Authority
(1996–2002). He has published extensively and has received
several academic and industry awards. His latest book is entitled
“Sustainable Shipping: A Cross Disciplinary View”(Springer,
2019).
Jingwen Qi is a Ph.D. student at the Department of Logistics and
Maritime Studies (LMS), The Hong Kong Polytechnic University
(PolyU). She is interested in shipping operations management,
green shipping, block-chain in shipping, and green shipping
policies. She aims to investigate the interrelationships between
decisions of different stakeholders in the maritime industry to
improve the efficiency of maritime and promote the environ-
mentally friendly and sustainable practices.
S. Wang et al. Communications in Transportation Research 1 (2021) 100005
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