FuelTrust’s AI-enabled solutions measure vessel carbon emissions
As shipping moves towards its 50% carbon reduction target in 2050, the progress of vessels in relation to this goal will be assessed based on historical baselines going back to 2008. Finance decisions, tax levies and ESG reporting will all be driven by this assessment of vessel performance and could result in major financial implications.
“Whether you’re calculating carbon emissions in support of CII, ETS, or your own ESG initiatives, producing detailed and accurate emission assessments is no longer a reasonable ‘nice to have’ goal or a ‘too hard to get’ response. With impending EU and ASEAN tax schemes coming in 2024, guesstimates or generic calculated reporting could leave you unfairly financially penalised,” warns Darren Shelton, chief product officer at software-as-a-service (SaaS) startup FuelTrust.
According to Shelton, shipowners with a detailed and verified baseline assessment of historical emissions, based on scientific analysis, will have a commercial advantage over those using current emissions models that can only estimate performance.
Last year, FuelTrust – headquartered in Houston, Texas, and co-founded by Shelton, a 27-year veteran of the maritime industry, and CEO Jonathan Arneault, a former IBM executive involved with the Watson AI technology – launched Carbon Baseline. The cloud-based solution uses an AI ‘Digital Chemist’ and blockchain technology to deliver a validated historic carbon baseline “in weeks, not months”.
With this validated historic carbon baseline, owners can increase charter pricing for validated green ships, certify applications for carbon credits, and with FuelTrust’s independent emissions scoring, seek lower carbon taxes and fees globally, says Shelton.
He adds: “Current emissions models offer only rough estimates based on generic calculator models that don’t account for chemical interactions, source fuel data, or supply and delivery chain impacts. Many also require massive amounts of manual input, or the installation of costly, high-maintenance devices aboard vessels.”
As an example, Shelton points to a shipowner client who had reported fleet emissions using the standard DCS emissions ratios. “When we examined their fuel lab results and operations data using our artificial intelligence technology, we discovered that the fuels they purchased, and the engines that burned them, produced at least 8% lower CO2 emissions than reported… and that was before any equipment and operational improvements. If they had to pay EU carbon taxes on a typical year’s European destination voyages based on their DCS analysis, they would have overpaid by more than €500,000 per year.”
The company’s patent-pending Digital Chemist uses historical operational data to calculate prior-year GHG emissions profiles for a vessel or fleet. Its AI algorithms provide calculations based on a simulation of combustion at a molecular level, which considers differences between batches of fuels, and deliver an assessment of fuel performance and regulatory compliance based on specific and actual vessel activity, rather than manufacturer and supplier specifications alone.
“Exact calculation is essential for the industry as not all fuels are created equal,” says Sheldon. “Recent studies have shown that, for example, there can be an energy density difference of up to 3% between batches of the same fuel. There is also a significant carbon difference between batches.
“By offering this higher level of granularity in our data, we can give owners and charterers a far better picture of what their GHG performance has been in the past and what will be in the future.”
Shelton continues: “With Carbon Baseline, class or flag authorities can be provided a more accurate, third-party verified report on the emissions reductions actually achieved, meaning the fleet owner, their customers and their investors can benefit.”
Carbon Baseline outputs a blockchain certificate for its findings, creating a fixed-in-time, immutable record. As explained by Jonathan Arneault, this makes it easier for fleets to apply for carbon credits, and the permissioned blockchain allows only authorised persons to view the data. “Blockchain allows companies to share information but not have it reshared…,” Arneault says, “…it gives really good privacy while at the same time allowing trust and transparency.”
Return on investments
Since Carbon Baseline can provide emission results from previous voyages, it not only helps to certify past emissions, but it can also help to verify the return on cleantech investments shipowners have made over time, such as adding a scrubber or hull coating. In March, FuelTrust announced results of its work with Ridgebury Tankers to validate emissions reductions for the maritime asset management firm’s fleet.
Using FuelTrust’s AI technology, Ridgebury has assessed fuel and operations data from past years for its Suezmax tanker Ridgebury John Zipser, comparing month-by-month and year-by-year performance to establish a baseline for carbon emissions, from which it could measure vessel improvements. The analysis also showed the value of a scrubber retrofit for the vessel and the impact of HFO fuel quality on carbon emissions.
According to Arneault, analysis using Carbon Baseline has helped Ridgebury to understand, to the kilogram, the entire emissions stack of the vessel, covering CO2, NOx, SOx, CAP and HAP emissions.
“At low cost, Ridgebury has been able to analyse the effects on vessel performance of installing a scrubber, a silicone hull coating, and buying higher quality fuels. The insights available to Ridgebury through FuelTrust’s technology would previously have been possible only by using an extensive and costly assortment of physical sensors and emissions-lab assessment consulting,” he says.
FuelTrust’s approach goes beyond simply applying a reduction in estimated emissions for each new piece of technology fitted to a vessel. The company uses AI-based virtual models of engines, scrubbers, coatings, and other clean technology when it analyses ship performance. The AI technology can switch a particular virtual technology ‘on’ or ‘off’ and observe outcomes for past and future investments. It can therefore provide insights into investments in technology, changes to operational practices and fuel choices, and accurately model the benefits of combining these decisions.
Building on this initial project with Ridgebury, FuelTrust is now analysing additional tankers to assess how fuel choice and operational behaviours could reduce emissions. As part of the next phase the firm will produce an analysis of the relative financial and environmental benefits that could be accrued through the installation and effective operations of a scrubber by model. The company will also provide insight into optimal HFO outcomes versus continued use of VLSFO without retrofit.
