Accurate data paramount as new emissions regulations kick in
Jonathan Arneult and Darren Shelton from FuelTrust write for Splash today.
Over the past five years, the shipping industry has undergone a significant shift towards sustainability, driven by new regulatory and commercial changes. These changes, such as emissions reporting, legislation of carbon taxes, implementation of Carbon Intensity Index (CII) ratings, and shifting measurements, have significant commercial impacts on owners, charterers, managers, and cargo shippers.
While the aspirations towards sustainability are high, the bills associated with achieving them can be astronomical. The only defence for the industry is richer, more accurate, and actionable data to make decisions and mitigate liabilities.
During the announcement of the maritime sector’s inclusion in the EU ETS from 2024, Peter Liese, the rapporteur for EU carbon market reform legislation, highlighted the significance of this to the industry. He stated that it would “encourage shipowners and operators to adopt the best available technology, and innovate.”
The inclusion of the maritime sector in the EU Emissions Trading Scheme (ETS) from 2024 is an important achievement, as it will encourage shipowners and operators to invest in greener technologies to avoid higher taxes and operating costs. However, there is a risk that shipping companies may end up paying more in carbon taxes than necessary due to the use of generic “Fuel Emissions Factors” that do not account for the actual emissions potential of individual fuel batches, carbon-reducing additives, or the effect of emissions reducing equipment.
According to research carried out by FuelTrust in 2022, more than 12,000 vessels over-reported their EU emissions by an average of 4.18%, with the figure ranging from 2% to 20%. Under the EU ETS, this means that shipping companies could end up overpaying more than €407m ($440m) for EU carbon taxes if the same voyages occurred in 2024.
Moreover, vessels with average CII scores could drive owners to invest millions of euros in certain ‘high promise’ cleantech hardware based on the idealised results of averaged emission factors. This commonly accepted approach risks an unintended outcome – there may actually be more global emissions generated as work is spread across more ships to gain a lower individual score, rather than lowering overall emissions for workload-tonnes delivered.
The use of typical emissions models that provide rough estimates for a vessel’s carbon output is not sufficient to achieve sustainability goals. These models use generic calculations that do not account for hull and mechanical investments, greener fuels (such as bio-blends, carbon-reducing additives, etc.), fuel chemical interactions, individual bunker data, or supply chain decarbonisation. Additionally, most methods require a significant amount of ongoing manual input or the installation and maintenance of costly devices aboard vessels, which can create a gap between the investment, the truth, and the return on investment. The solution lies in more detailed data and provides value for doing the right thing based on the actual outcomes of actions, while also itemising those results in required reporting.
Companies can use richly detailed data to determine the actual emissions by looking at the fuel lab-data and their workload outcomes. Ridgebury Tankers recently took this approach with FuelTrust and found that their vessel improvement investments and fuel purchase choices resulted in over three times the carbon reduction that the standard emissions formulas provided, not to mention the significant fuel savings they gained.
The challenge is to find a balance between the regulations that incentivise sustainability and the practical considerations of the industry which benefits the global supply chain, and the humans which it serves.
The shipping industry continues to innovate and invest in green technologies to reduce carbon emissions and meet regulatory requirements. At the same time, regulators need to enable the accurate and effective methods of measuring emissions that consider the nuances of individual fuel batches and the impact of emissions reducing equipment and additives. In the end, the solution lies in data-driven decision-making.