Platform for Advanced Emissions Calculations
A sample screenshot of VesselBot’s platform, showing: (top) an interactive graph that visualizes trends in a company’s emissions, including total tons, intensity, and weight, across days, months, and years; (middle) an interactive graph that displays trends in emissions intensity by mode of transportation over days, months, and years; and (bottom) pie charts that illustrate emissions (total tons), intensity, shipment weight, and distance traveled, categorized by mode of transportation.
By Constantine Komodromos
In today’s increasingly regulated shipping environment, accurate measurement of maritime emissions has evolved from a mere sustainability goal to a critical business requirement, especially for shippers. With the implementation of the European Green Deal, the Science-Based Targets initiative (SBTi, a corporate climate action organization), and the International Maritime Organization’s ambitious targets to reduce carbon intensity by 40 percent by 2030, shipping companies face mounting pressure to provide precise emissions data.
The challenge, however, goes beyond simple compliance. Default values and industry averages—the traditional approach to emissions calculation—fail to capture the complex dynamics of modern maritime operations. Each voyage is subject to unique conditions: varying weather patterns, specific vessel characteristics, fuel types and operational decisions all dramatically impact the actual carbon footprint of maritime transportation.
This data gap represents not just a regulatory challenge but a significant obstacle to meaningful climate action in one of the world’s most carbon-intensive industries. It’s within this context that VesselBot has developed its Supply Chain Sustainability Platform, ranked #1 in Drewry’s Emissions Measurement Providers Comparison Guide for 2024, with a remarkable score of 9.89 out of 10 for ocean freight emissions calculations.
The Power of Primary Data
The foundation of VesselBot’s approach is the prioritization of primary data—real-time, specific information collected directly from the source. Unlike conventional methods that rely on default values and generalized assumptions, VesselBot integrates actual operational data to incorporate transport-specific, route-specific, and fuel-specific values.
“Companies must use data that is most representative of the actual fuel and energy consumption,” states the SBTi, highlighting the importance of this approach.
Similarly, the GHG Protocol, comprising comprehensive global standardized frameworks to measure and manage greenhouse gas (GHG) emissions from private and public sector operations, value chains and mitigation actions, prioritizes primary data for its accuracy and reliability, and the European Sustainability Reporting Standards require companies to disclose their materials’ impact using “primary data obtained from suppliers or other value chain partners.”
VesselBot’s Supply Chain Sustainability Platform captures five critical primary data elements that directly affect emissions calculations. One is actual distances traveled, using real-time AIS tracking systems rather than straight-line, port-to-port minimum feasible distance calculations. Another is vessel-specific characteristics, including size, type, deadweight tonnage, engine and propeller data, fuel type, and capacity. A third is real-time utilization rates, measuring how many containers are being carried on each voyage. A fourth is precise fuel consumption, based on vessel operations, speed and engine performance. A fifth is weather conditions, incorporating real-time weather data that can significantly impact fuel usage.
The difference from conventional methods is substantial. For example, during Hurricane Milton in 2024, vessels diverted from their planned routes in the Gulf of Mexico faced both longer journeys and challenging weather conditions. VesselBot’s calculations showed that these diversions and weather impacts significantly increased fuel consumption as shipping companies struggled with unexpected increases to navigate longer or less direct paths. These variations in fuel consumption and emissions due to weather and rerouting are completely missed by default calculation methods that don’t incorporate real-time operational data.
Hurricane Milton’s path and voyage disruption during the period of October 8 to October 10, 2024. Calculated vessel density shows how ships diverted to avoid affected areas of Florida.
The Core of Advanced Maritime Data Processing
At the heart of VesselBot’s technology lies an innovative application of digital twin modeling. These digital twins create dynamic, advanced simulations of real-world physical parameters, systems, and processes related to maritime transportation, enabling precise emissions calculation and optimization.
With digital twins for more than 40,000 vessels, VesselBot maintains an extensive virtual fleet that mirrors the exact characteristics of ships in real-world conditions, providing accurate models for emissions calculations. This model incorporates: vessel characteristics—size, type, deadweight tonnage, fuel type, engine characteristics, propeller characteristics, drafts and total TEU capacity; voyage information—departure and arrival ports, speeds per waypoint, duration, intermediate stops, rerouting data, and anchorage and berth time; vessel performance—speed, draft, engine power required per waypoint, fuel consumption, weather impact and vessel utilization; and telematics—AIS position data for real-time tracking and monitoring.
Digital twin technology enables VesselBot to calculate emissions with unprecedented accuracy while providing a continuous feedback loop that allows for dynamic updates based on changing conditions.
The Supply Chain Sustainability Platform handles everything automatically, from data collection across the entire carrier network to data cleansing, harmonization and analysis—delivering actionable intelligence without requiring manual intervention.
Red Sea Crisis Response
The 2024 Houthi attacks in the Red Sea created significant disruptions to global shipping routes, forcing carriers to divert around the coast of Africa and the Cape of Good Hope. VesselBot’s data processing systems monitored this situation in real time, capturing how these longer routes affected delivery times and emissions.
Our analysis found that goods arriving in Europe faced an average 15-day delay when rerouting around the Cape of Good Hope. More critically, total GHG emissions increased significantly while emissions intensity (gCO2e/km TEU) remained relatively stable, indicating that despite the operational challenges, carriers maintained efficiency in their extended voyages.
By incorporating geospatial data into its algorithms VesselBot manages to capture all significant geopolitical and trade pattern changes that occur, such as the Houthi attacks that have caused a 73.12 percent reduction in container vessel traffic through the Suez Canal in 2024 compared to the previous year. These types of changes, apart from the direct trade consequences that they cause, bring significant changes to the emissions output of the global fleet. Therefore, shippers that have a real-time depiction of such incidents can utilize the intelligence gained to make informed data-driven decisions about alternative schedules and route planning and more accurately communicate expected delivery times and environmental impacts to their customers.
Weather Impact Analysis at Scale
In February 2024, a severe winter storm brought heavy snow and ice to ports of Northern Europe, affecting Rotterdam and Hamburg. VesselBot’s systems captured how extreme cold and poor visibility hampered port operations, leading to significant delays in cargo handling and a buildup of ships waiting to enter the ports.
By processing weather data alongside vessel positioning information, our platform quantified the additional emissions generated by these delays. For the Netherlands’ ports alone, cumulative emissions related to anchored times equaled 31,336.05 tons in 2024.
Integrating Communications and Telemetry For Advanced Emissions Management
VesselBot’s Supply Chain Sustainability Platform doesn’t operate in isolation—it seamlessly integrates with existing communications and telemetry systems, creating a unified data ecosystem for emissions management.
The platform utilizes multiple data sources to give shippers complete visibility: shipment tracking data—automatic collection of transportation data across all carriers in a shipper’s network, providing complete visibility of goods movement; emissions calculations—precise calculations of emissions for each shipment based on vessel-specific performance characteristics rather than industry averages; weather impact analysis—incorporation of weather data to understand how external conditions affect shipment timelines and associated emissions; and port performance metrics—information about port operations that helps shippers understand congestion and delays affecting their cargo and emissions profile.
Beyond data collection, VesselBot’s platform transforms complex data into clear insights that shippers can immediately act upon. Carrier performance dashboards provide comprehensive visualizations that enable shippers to compare emissions performance across their carrier network and make more sustainable decisions. Compliance reporting is done via automated generation of emissions reports to satisfy regulatory requirements and support sustainability disclosures for shippers’ Scope 3 emissions. Transportation optimization is achieved through actionable insights that help shippers select more efficient routes, modes and carriers to reduce emissions while maintaining optimal service levels. Supply chain collaboration is enabled via a shared information platform that facilitates shippers work with their carriers and suppliers to collectively address emissions challenges.
The Evolution of Maritime Data Processing
As the maritime industry continues its decarbonization journey, the role of advanced data processing will only grow in importance. Looking ahead, several trends are likely to shape the future of emissions calculation, reporting and optimization. One is the integration of alternative fuel data: As the adoption of LNG, methanol, ammonia and hydrogen increases, data systems must evolve to accurately track the complex emissions profiles of these fuels across their entire life cycle. Another is predictive analytics for emissions forecasting: Machine learning algorithms will increasingly leverage historical emissions data to predict future patterns, enabling proactive emissions management. A third is regulatory convergence around primary data: As regulators recognize the limitations of default values, reporting requirements will increasingly mandate the use of primary data for emissions calculations.
VesselBot’s platform, with its foundation in primary data collection and digital twin technology, is well-positioned to evolve alongside these industry trends. The system’s ability to integrate multiple data sources makes it adaptable for alternative fuel tracking as the industry transitions. Its communications infrastructure supports enhanced port-vessel coordination, while the comprehensive data modeling capabilities across more than 40,000 vessel digital twins provides a robust foundation for advanced analytics. As regulatory frameworks increasingly emphasize primary data—the approach VesselBot has championed from the beginning—the platform offers a future-proof solution for maritime emissions management.
The challenge of maritime decarbonization is, at its core, a data challenge. Without accurate calculations, stakeholders cannot effectively manage their environmental impact or make informed decisions about efficiency improvements.
VesselBot’s state-of-the-art technology, combining primary data collection, digital twin modeling and advanced data processing, represents a significant advancement in addressing this challenge. By providing unprecedented precision in maritime emissions calculation, reporting, and optimization, the platform enables shippers, cargo owners, and carriers to move beyond compliance and toward meaningful climate action.
What sets VesselBot apart is its frictionless approach to data management. With a single connection to its Supply Chain Sustainability Platform, customers gain access to a fully automated system that handles everything from data collection to analysis, with no manual data entry required. The platform’s nearly perfect score in Drewry’s evaluation (9.89 for ocean freight) underscores the exceptional accuracy and capability of this approach.
As regulatory pressures increase and stakeholders demand greater transparency, the value of accurate emissions data will only grow. The future of sustainable shipping depends not just on technological innovations in vessel design and alternative fuels, but on the sophisticated data systems that enable their effective deployment.
Through continued innovation in communications, telemetry and data processing, VesselBot is committed to supporting the maritime industry’s transition to a low-carbon future—one accurate measurement at a time.
