Methodology for rating the operational energy efficiency performance of ships in the context of global climate governance

doi:10.12006/j.issn.1673-1719.2020.048

Abstract

Abstract:

In a joint effort to address global climate change, the International Maritime Organization (IMO) has considered imposing a regulatory regime on the operational energy efficiency of ships to complement the existing mandatory mechanism on design efficiency. However, the random and uncertain nature of the operational energy efficiency of ships poses a significant challenge to performance regulation. In this paper, a quantile regression model, with dummy variables representing the observation calendar years, is applied to quantify the level, the scale and the skewness of the distribution of the operational carbon intensity performance of international shipping. A rating mechanism is further constructed on this basis, which is able to guide the performance of international shipping as a whole in line with the levels of ambition, whilst being robust to certain individual deviations. This rating mechanism is demonstrated using the bulk fleet of China as a sample, which shows its competency as a systematic solution for scientific evaluation of the operational energy efficiency of ships.

Key words: Operational energy efficiency, Greenhouse gas emissions reduction, Carbon intensity, Rating mechanism, International Maritime Organization (IMO)

ZHANG Shuang, ZHAO Ying-Lei, ZHANG Kun-Kun, LI Lu. Methodology for rating the operational energy efficiency performance of ships in the context of global climate governance[J]. Climate Change Research, 2021, 17(2): 236-244.

Figures/Tables 8

Fig. 1 A five-grade rating mechanism for operational energy efficiency of ships

Fig. 2 dd vectors and the boundaries for defining rating bands

Table 1 Description of the sample ships

Table 2 Scale and skewness of the middle 30% and 70% of the carbon intensity distribution

Table 3 Estimates of the dd vectors and the equivalent percentage change

Table 4 Estimates of the median and the parameters for determining rating boundaries (in logarithmic form and original form)

Fig. 3 Rating results based on EEOI in (a) 2015-2017, (b) 2018

Table 5 Proportion of ships rated as each grade %

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