In recent years, reducing emissions from maritime transport has become a priority for many port cities. Indeed, ships are a significant source of pollutants such as carbon dioxide (CO2), nitrogen oxides (NOx), sulphur dioxide (SO2), particulate matter (PM) and other pollutants that contribute to air pollution and climate change. The problem is particularly relevant in ports, where ships spend long periods at berth with their engines running to keep on-board systems running, an operational phase known as hoteling. To address this problem, there are different methods of monitoring ship emissions. One approach is direct monitoring, which involves the use of sensors that are installed on ships or in the vicinity of port areas to measure the amount of pollutants being emitted. Although it provides very accurate data, this approach involves high costs and requires specialized equipment. Another methodology is the fuel consumption-based emission inventory, which uses data declared by ship operators. However, this approach may be affected by inconsistencies in reporting and does not always provide precise emission estimates for specific ship activities and operating conditions. In this work, emissions are estimated using available data, including technical characteristics (such as gross tonnage, engine power, etc.) and ship operational information (such as arrival and departure times, dwell time, etc.). Special attention is paid to the time at hoteling, i.e. the period during which the auxiliary engines remain active while the ship is at hoteling, as it contributes significantly to the total emissions. The estimation is based on regression curves and considers variables such as load factor and pollutant-specific emission factors. The necessary information was obtained from databases such as the Automatic Identification System (AIS) and international studies. In this context, the port of Catania was chosen as a case study to analyze the contribution of Ro-Ro ships to local emissions. This type of ship, used to transport vehicles and rolling stock, is among the main sources of pollution. Estimates show that fuel consumption and emissions vary significantly depending on the size and frequency of ship trips, highlighting the importance of targeted strategies to reduce environmental impact. This analysis thus provides a useful framework for understanding the dynamics of maritime pollution and represents a first step towards a more detailed and in-depth quantification of emissions, taking the selected case study as a reference.
Assessing Ship Emissions: An Estimation Approach Applied to the Port of Catania (Italy) / Barbagallo, Antonio; Torrisi, Vincenza; Ricci, Stefano; Twrdy, Elen; Ignaccolo, Matteo. - 15897 LNCS:(2026), pp. 117-130. ( Workshops of the International Conference on Computational Science and Its Applications, ICCSA 2025 Istanbul ) [10.1007/978-3-031-97660-5_9].
Assessing Ship Emissions: An Estimation Approach Applied to the Port of Catania (Italy)
Ricci, Stefano;
2026
Abstract
In recent years, reducing emissions from maritime transport has become a priority for many port cities. Indeed, ships are a significant source of pollutants such as carbon dioxide (CO2), nitrogen oxides (NOx), sulphur dioxide (SO2), particulate matter (PM) and other pollutants that contribute to air pollution and climate change. The problem is particularly relevant in ports, where ships spend long periods at berth with their engines running to keep on-board systems running, an operational phase known as hoteling. To address this problem, there are different methods of monitoring ship emissions. One approach is direct monitoring, which involves the use of sensors that are installed on ships or in the vicinity of port areas to measure the amount of pollutants being emitted. Although it provides very accurate data, this approach involves high costs and requires specialized equipment. Another methodology is the fuel consumption-based emission inventory, which uses data declared by ship operators. However, this approach may be affected by inconsistencies in reporting and does not always provide precise emission estimates for specific ship activities and operating conditions. In this work, emissions are estimated using available data, including technical characteristics (such as gross tonnage, engine power, etc.) and ship operational information (such as arrival and departure times, dwell time, etc.). Special attention is paid to the time at hoteling, i.e. the period during which the auxiliary engines remain active while the ship is at hoteling, as it contributes significantly to the total emissions. The estimation is based on regression curves and considers variables such as load factor and pollutant-specific emission factors. The necessary information was obtained from databases such as the Automatic Identification System (AIS) and international studies. In this context, the port of Catania was chosen as a case study to analyze the contribution of Ro-Ro ships to local emissions. This type of ship, used to transport vehicles and rolling stock, is among the main sources of pollution. Estimates show that fuel consumption and emissions vary significantly depending on the size and frequency of ship trips, highlighting the importance of targeted strategies to reduce environmental impact. This analysis thus provides a useful framework for understanding the dynamics of maritime pollution and represents a first step towards a more detailed and in-depth quantification of emissions, taking the selected case study as a reference.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


