Craig Jallal writes for Riviera on managing tank coatings under the CII regime.
Formulation of the CII rating
Why formulation of the CII rating may have unintended consequences for tank cleaning.
The development of the Carbon Intensity Indicator (CII) was predicated on assessing the whole of the shipping fleet, but as Lighthouse Maritime Services head of operations, Ace Trinidad, explained during the 12 April 2023 Riviera Maritime Media webinar, Advancing tank coatings management: technologies and vessel optimisation, it could fundamentally change the way the chemical carrier fleet manages tank cleaning.
At a basic level, CCI is essentially the emissions that a vessel produces in a year divided by the vessel deadweight (the denominator) and the distance that it sailed throughout the year (the numerator).
“It is not as simple as that in the formula, because there are exclusions and there are also correction factors,” Mr Trinidad explained. “The correction factors and exclusions are there to provide a level playing field for all kinds of ships,” he said. For example, there is a correction factor included to allow for higher fuel consumption for vessels sailing in ice conditions.
Breaking down the formula, he noted that CFj is the conversion factor for CO2 applied to the total fuel consumption (FCj). That is, all the fuel consumptions above the line, multiplied by the CO2 conversion factor.
Series of exclusion factor
There are a series of exclusion factors, including FCvoyage, which is the aforementioned ice sailing conditions: when applied, these remove the fuel oil consumed from the total fuel consumption (FCj).
Mr Trinidad noted that there are three exclusions that are relevant to tank operations: fuel consumed to produce electrical energy (FCelectrical for instance for the cargo pumps); FCboiler (fuel used for the boiler (to heat cleaning water); and FCothers, which as the terms suggests, is a sweeper for miscellaneous fuel use.
Below the line, the denominator is distance multiplied by capacity. But distance has some modifiers, including extra distance travelled to avoid dangerous situations. The capacity, deadweight, is a constant without any modifiers.
“Tank cleaning is relevant in the CII,” said Mr Trinidad, “through various scenarios and how these apply to the formula. The only three parameters that will change will be the fuel consumption throughout the year, the exclusions and the distance. And remember, the higher the result of the calculation, the worst the CII rating,” he said.
As a remainder, CII ratings run from A to E, with E being the worse. If a vessel has a higher fuel consumption in a year when exemptions and distance are the same, the resulting CO2 calculation will be higher, and the CII rating will be worse – B to C, or C to D and so on.
If a longer distance is sailed for the same fuel consumption, then the calculation produces a lower CO2 consumption and the rating will improve – from D to C for instance.
“But notice that excluded fuel consumption is subtracted from the total fuel consumption,” said Mr Trinidad, “The more excluded fuel consumption, the CI seems to become better.”
Mr Trinidad noted that the unintended impact of the CII formulation is that the more the boiler is used to produce hot water to clean the cargo tanks, the FCboiler improves the CII.
“If that is the case, it looks like the more we clean, the CII becomes better,” said Mr Trinidad. “It looks like an anomaly in the CII formula: when you are trying to reduce emissions; CII (forces) opposite behaviour,” he said.
Negative impact on the CII
The normal scenario is for the chemical carrier to arrive at a port and then drift for two weeks while undertaking cleaning operations. Fuel will be consumed by the boiler and generators, but very little distance covered in that time. This has a large, negative impact on the CII.
The lesson to be learnt is that under the CII environment that commenced at the start of 2023, if at all possible, clean tanks while underway to optimise the CII rating.
Consulex principal consultant D. Terry Greenfield, took up challenge of placing artificial intelligence (AI) in the space of tank cleaning. “AI learns from the input that we provide, and learns from the decisions that are made again and again, good and bad,” he said. “The (AI) system is predictive and it works forward to develop maintenance, for example.”
To be efficient, the AI tool needs massive amounts of data, and Mr Greenfield suggested the marine coatings industry needs to embrace some form of data sharing to optimise the use of AI. “A commonality and a trust [is needed] to be able to share a lot of that information, to make better decisions,” he said
He noted that there are hurdles to overcome in the application of AI to marine coatings, but it is a great opportunity to take a real step forward.
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Source: Riviera
