An Approach for Shipping Emissions Estimation in Ports: The Case of Ro–Ro Vessels in Port of Vigo

Citation: Albo-López, A.B.; Carrillo, C.; Díaz-Dorado, E. An Approach for Shipping Emissions Estimation in Ports: The Case of Ro–Ro Vessels in Port of Vigo. J. Mar. Sci. Eng. 2023,11, 884. https:// doi.org/10.3390/jmse11040884 Academic Editor: Hong Yang Received: 14 March 2023 Revised: 18 April 2023 Accepted: 19 April 2023 Published: 21 April 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Journal of Marine Science and Engineering Article An Approach for Shipping Emissions Estimation in Ports: The Case of Ro–Ro Vessels in Port of Vigo Ana B. Albo-López * , Camilo Carrillo and Eloy Díaz-Dorado Department of Electrical Engineering, University of Vigo, 36 310 Vigo, Spain; [email protected] (C.C.); [email protected] (E.D.-D.) *Correspondence: [email protected] Abstract: Despite most atmospheric emissions being produced by vessels when navigating at sea, they are also important when in port because of their proximity to urban areas and their harmful effects on climate change and health. First, we carried out a bibliographical review of the nine most relevant methods to estimate the emission of ships in ports. These methods have been used to estimate the emissions of the sixteen most representatives Ro–Ro (roll-on–roll-off) ships calling at the Port of Vigo. From the results obtained, a new simplified method for estimation is proposed, which is based on linear regression curves and takes into account the number of ships and the average number of hours they remain in port annually. This simplification could be a useful tool when making preliminary assessments of the emissions from ships in port, which can also be extrapolated to other ports or types of ships. Keywords: ship emissions; Ro–Ro ships; gross tonnage; fuel consumption; hoteling 1. Introduction Atmospheric emissions from ships during a voyage come mainly from their main engines [ 1 ]. While in port, however, they mainly come from the auxiliary engines (AE), which are used to produce power in loading, unloading and hoteling operations [2–5]. Although the quantity of emissions during this port stage is lower than during the voyage stage, the environmental pollution directly affects nearby population centers [6]. Carbon dioxide (CO 2 ) is the most important pollutant regarding greenhouse gas (GHG) emissions. However, special attention should also be paid to the presence of other atmospheric pollutants in port cities due to their impact on human health [ 7 , 8 ]: particulate matter (PM), volatile organic compounds (VOCs), carbon monoxide (CO), nitrogen oxides (NOx) and sulfur oxides (SOx). According to the European Maritime Safety Agency (EMSA) report for 2021 [ 9 ], the most important emissions from ships stopping in ports in the European Union (EU) or in the European Economic Area were CO 2 (Table 1). Furthermore, around 40% were produced by voyages between ports of EU Member States, this being 6% when ships are at berth. Table 1. Emissions by pollutant (t) of vessels calling at EU ports (2018–2019) [9]. Pollutant Type Emissions (106t) CO2140 SO21.63 NO24.46 PM2.5 0.26 There is a great need for analyses of emissions from ships during their stay in ports and also for the establishment of measures to reduce them; according to some studies [ 7 – 9 ]: •A total of 70% of ship emissions are estimated to occur within 400 km of land; J. Mar. Sci. Eng. 2023,11, 884. https://doi.org/10.3390/jmse11040884 https://www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2023,11, 884 2 of 20 •A total of 90% of European ports are spatially connected to cities; • The harmful effects of these pollutants affect almost 40% of the European population, who live within 50 km of the sea. For these reasons, the norms on controlling ship emissions in port are increasingly restrictive: • Internationally, they are regulated by Annex VI of the MARPOL Convention “Prevention of Air Pollution from Ships” added to the 1997 Protocol of the International Maritime Organization (IMO). This establishes a progressive reduction in SO x , NO x , and PM emissions and the introduction of emission control areas (ECAs) [ 10 ]. Amendments to this Annex VI were carried out in 2021 in order to reduce de GHG emissions from ships. These amendments require ships to improve their energy efficiency to reduce their emissions. From 1 January 2023 it is mandatory for all ships to calculate their attained Energy Efficiency Existing Ship Index (EEXI) to measure their energy efficiency and to initiate the collection of data for the reporting of their annual operational carbon intensity indicator (CII) and CII rating [11]. • At a European level, Directive (UE) 2016/802 [ 12 ] sets the reduction in the sulfur content of certain liquid fuels. More specifically, Article 7 sets a limit of 0.1% of sulfur content by mass for marine fuels used by ships in port, unless they are berthed for less than two hours or they switch off all their engines because they are connected to the shore-side electricity supply. With respect to greenhouse gas emissions, Regulation (UE) 2015/757 [ 13 ] established the monitoring, reporting and verification of carbon dioxide emissions from maritime transport. However, the biggest commitment of the European Union was adopted from 2019 with the European Green Deal [ 14 ] developed by European Climate Law [ 15 ] and the package of proposals ‘Fit for 55 0 [ 16 ] in 2021. These documents have set ambitious targets for reducing net emissions by at least 55% by 2030 compared to 1990 and for achieving the climate neutral by 2050. These proposes include the maritime sector in an emissions trading scheme and develop the Fuel EU Maritime initiative, which aims to increase the demand for use of renewable and low-carbon fuels and reduce their greenhouse gas emissions. Therefore, these norms limit the type of fuel used in ships and also their engines, which also has repercussions on consumption and pollutant emissions. For example, these parameters are essential for: •Analyzing any emissions reduction measure; •Simulating the dispersion of air pollution [17]; • Introducing new fuels with low or zero sulfur content (liquid natural gas, methane– methanol, hydrogen, and ammonia) and incorporating batteries and renewable systems in ships [18,19]; • Supplying electricity to the ship in port [ 20 ] (through an electrical micro-grid that can manage renewable energy production, the use of fuel cells and batteries and supply from the electricity grid; •Implementing a Smart Port [21]. Emissions from ships can currently be estimated by: • Data that the Automatic Identification System (AIS) transmits on each ship: IMO identification number, size, weight, name, type, position, speed, heading, etc. This system was passed by the IMO in 2002 and is mandatory on ships covered by the Convention of Safety of Life at Sea (SOLAS) to improve safety and efficiency of navigation [7]; • Technical information obtained from the IT database of Lloyd’s Register of Shipping (LRS), port authorities’ databases, engine ship manufacturers, ship owners, etc. [22]. This article aims to undertake a bibliographical review of the various methods existing to estimate the emissions from ships in port in order to: • Analyze and compare the different methodologies used in the calculation of emissions from ships during their stay in port, through the analysis of a specific case correspond- J. Mar. Sci. Eng. 2023,11, 884 3 of 20 ing to the Ro–Ro ships that call at the Port of Vigo. These ships were selected because of their importance for this port in cargo traffic [ 23 ], and because the number of hours of Ro–Ro ships stayed in 2018 was about 16 times higher than those for transatlantic vessels [24,25]; •Establish a simplified calculation of emissions from ships in port. 2. Methodology This section contains the most relevant methods to estimate emissions from ships during their stay in ports taken from the bibliographical review undertaken. These emissions can be obtained from the power of the ship’s auxiliary engines or from fuel consumption. As this information is not generally available, it is estimated from the gross tonnage (GT), usually by using regression curves [ 4 , 5 ]. This GT parameter is freely accessible on several shipping websites. According to Figure 1, the methods analyzed in this article can be classified into three groups: •Methods A: Calculate emissions from the estimated power of the auxiliary engines; • Methods B: Obtain emissions through the fuel consumption estimated from the power of the auxiliary engines; • Methods C: Calculate emissions from estimated fuel consumption directly through the GT. J. Mar. Sci. Eng. 2023, 11, x FOR PEER REVIEW 3 of 22 Emissions from ships can currently be estimated by: • Data that the Automatic Identification System (AIS) transmits on each ship: IMO identification number, size, weight, name, type, position, speed, heading, etc. This system was passed by the IMO in 2002 and is mandatory on ships covered by the Convention of Safety of Life at Sea (SOLAS) to improve safety and efficiency of navigation [7]; • Technical information obtained from the IT database of Lloyds Register of Shipping (LRS), port authorities databases, engine ship manufacturers, ship owners, etc. [22]. This article aims to undertake a bibliographical review of the various methods existing to estimate the emissions from ships in port in order to: • Analyze and compare the different methodologies used in the calculation of emissions from ships during their stay in port, through the analysis of a specific case corresponding to the Ro–Ro ships that call at the Port of Vigo. These ships were selected because of their importance for this port in cargo traffic [23], and because the number of hours of Ro–Ro ships stayed in 2018 was about 16 times higher than those for transatlantic vessels [24,25]; • Establish a simplified calculation of emissions from ships in port. 2. Methodology This section contains the most relevant methods to estimate emissions from ships during their stay in ports taken from the bibliographical review undertaken. These emissions can be obtained from the power of the ships auxiliary engines or from fuel consumption. As this information is not generally available, it is estimated from the gross tonnage (GT), usually by using regression curves [4,5]. This GT parameter is freely accessible on several shipping websites. According to Figure 1, the methods analyzed in this article can be classified into three groups: • Methods A: Calculate emissions from the estimated power of the auxiliary engines; • Methods B: Obtain emissions through the fuel consumption estimated from the power of the auxiliary engines; • Methods C: Calculate emissions from estimated fuel consumption directly through the GT. Figure 1. Methods to estimate emissions from ships in port [5,26–36]. 2.1. Emissions Estimate from Ship’s Auxiliary Engines Power Generally, the calculation for commercial ships is done on the basis of the emissions for each voyage in the different phase of trip: cruise, maneuvering and hoteling. 𝐸 =𝐸  +𝐸  +𝐸  (1) Figure 1. Methods to estimate emissions from ships in port [5,26–36]. 2.1. Emissions Estimate from Ship’s Auxiliary Engines Power Generally, the calculation for commercial ships is done on the basis of the emissions for each voyage in the different phase of trip: cruise, maneuvering and hoteling. ETrip =ECruising +EManeuvering +EHoteling (1) This article only considers the third term in Equation (1), as the estimation will be made based on the following aspects: • During their stay in port, the ships use their auxiliary engines (AE) to produce electricity in loading, unloading and hoteling operations [2–4]; • Because Vigo is a European port, engines can only use marine fuel with a limit of 0.1% sulfur content by mass such as marine gas oil (MGO) of 0.1% [12]; • The type of diesel engine for Ro–Ro ships will be considered as medium-speed [ 4 , 37 ]. During the ships’ stay in port, the emissions estimation method for their AEs and each pollutant takes into account the time the AEs operate for each type of ship, their power, time hoteling, load factor and emissions factor for each pollutant being considered [ 5 , 26 , 37 – 39 ]. EHoteling,i=Th·PAE·LFAE·EFi 103(2) J. Mar. Sci. Eng. 2023,11, 884 4 of 20 where: •EHoteling,i: emission for hoteling (t) of “i” pollutant; •i: pollutant (NOx, SO2, CO2, VOC, PM, CO, N2O); •Th: time for hoteling (h); •PAE: auxiliary engine nominal power (kW); •LFAE: auxiliary engine load factor (Table 2); •EFi: emission factor of “i” pollutant (kg/kW). Table 2. Calculation methods for the auxiliary engine power for hoteling of Ro–Ro ships as a function of GT. Method PME (kW) Ratio AE/ME LFAE 2010 World fleet 164.578·GT0.4350 (3) 0.24 0.4 1997 World fleet 35.93·GT0.5885 (4) N/A 0.4 2006 Mediterranean Sea fleet 45.7·GT0.5237 (5) 0.39 0.4 Wang 692.09·GRT0.2863 (6) N/A N/A Oviedo UF 206.1793 · GT 0.3967 (7) N/A 0.4 Other sources also consider other factors for adjustment: • When the engines work at low load [ 40 ], in order to obtain the increase in emissions for this situation, in the case of auxiliary engines, this factor is considered to be 1, which means it does not affect the estimate; • In order to reflect environmental benefits obtained by installing emission reduction technologies in the ship and/or engines [ 8 , 41 ], this factor will not be applied in this article. •Therefore, regarding the parameters defined in Equation (2), it can be seen that: • The emission factors were taken from the reports by ENTEC 2010 [ 37 ] (Table 3), USA EPA 2009 [4] (Table 4) and Port of Los Angeles 2020 [42] (Table 5); • The number of hours the ships are in port (T h ) was obtained from the analysis of Ro–Ro ships in the Port of Vigo (Section 3.1); • No information was available on either the auxiliary engines’ power or their load factors. Table 3. AE emission factors (g/kWh) for hoteling ENTEC 2010 [37]. Engine/Fuel Type NOxPre-2000 Engine NOxPost-2000 Engine NOxFleet Average SO2CO2VOC PM10 PM2.5 SFC * Medium–highspeed/MGO 13.9 11.5 13.0 0.9 690 0.4 0.3 217 * SFC: Specific fuel consumption. Table 4. AE emission factors (g/kWh) for hoteling USA EPA 2009 [4]. Fuel Type NOxPM10 PM2.5 SOxCO2VOC CO SFC 0.1% MGO 13.9 0.18 0.17 0.42 690.71 0.4 1.1 217 Table 5. AE emission factors (g/kWh) for hoteling, Port of Los Angeles 2020 [42]. Engine/Fuel Type Tier NOxPM10 PM2.5 SOxCO2VOC CO N2O CH4 Medium-speed/0.1% MGO 1 12.2 0.19 0.17 0.42 696 0.4 1.1 0.029 0.008 2 10.5 High-speed/0.1% MGO 1 9.8 0.9 2 7.7 J. Mar. Sci. Eng. 2023,11, 884 5 of 20 Regarding this final point, various methods were encountered in the bibliographical review on the methodology for estimating ship emissions (Table 2), which obtain the main engines power (PME)according to GT by means of non-linear regression curves. All the methods use GT, except Wang [ 27 ], who used gross registered tonnage (GRT). The equivalence between GRT and GT is 1 GT = 1.875 GRT [ 5 ]. GRT was substituted by GT when the IMO adopted the International Convention on Tonnage Measurement of Ships on 23 June 1969. Moreover, auxiliary engine power for hoteling is obtained according to main engine power, the estimated average vessel ratio of auxiliary engines/main engines (AE/ME), and the % load of MCR (maximum continuous rating) of auxiliary engines for hoteling (LF AE ). 2.2. Emissions Estimate from Auxiliary Engines Fuel Consumption The emissions for each pollutant obtained from auxiliary engines’ fuel consumptions and the emission factors for each pollutant for hoteling are shown in Tables 6and 7. [ 5 , 38 , 43 ]. EHoteling,i=Th·FC·EFi 103(8) where: •EHoteling,i: emission for hoteling (t) of “i” pollutant; •Th: time for hoteling (h); •FC: fuel consumption (tfuel/h); •EFi: emission factor of “i” pollutant (kg/tfuel). Table 6. Tier 1 engine emission factors (kg/t) for hoteling [38,43]. Fuel Type NOxCO NMVOC * SOxPM10 PM2.5 MDO-MGO 78.5 7.4 2.8 20 1.5 1.4 * NMVOC: Non-methane volatile organic compounds. Table 7. Tier 2 engine emission factors (kg/t) for hoteling [38,43]. Engine/Fuel Type NOx2000 NOx2005 NOx2010 CO NMVOC SOxPM10 PM2.5 Medium-speed/MDO-MGO 65.0 63.1 60.6 7.4 2.8 20 1.5 1.3 High-speed/MDO-MGO 59.1 57.1 55.1 Emission factors for auxiliary engines and marine gas oil (MGO) were taken from Trozzi [ 38 , 43 ]. However, marine diesel oil (MDO) is also inclued in the fuel type. Even though emissions factors for further pollutants may exist, the analysis focuses on those that are similar to those obtained from auxiliary engine power, and that have the most relevant effects, as mentioned in the introduction (Table 6). In this case, data for fuel consumption do not exist either, but they can be estimated theoretically by means of different methods according to GT or auxiliary engines power (Table 8). Table 8. Calculation methods for fuel consumption (FC) of Ro–Ro ships as a function of GT or PAE. Method FC (tfuel/h) Method 1999—Trozzi and Vaccaro (12.834+0.00156·GT)·pm 24 (9) Method 2006—Trozzi and Vaccaro (6.3501+0.0013·GT +1.6852E−7GT2−6.2691E−12·GT3+5.699 E−17·GT4)·pm 24 (10) Schrooten and Goldsworthy SFC·LFAE ·PAE 106(11) Fuentes GarcíaHV·LFAE ·PAE 103(12) where: J. Mar. Sci. Eng. 2023,11, 884 6 of 20 • p m : The fraction of maximum fuel consumption for different operation modes, taking into account a 0.2 value for hoteling default [28–34]; • SFC: Specific fuel consumption (g/kWh). Taking into account a mediumor highspeed diesel engine that uses marine gas oil as fuel, its hoteling-specific consumption would be 217 (g/kWh) for auxiliary engines [38]. • LF AE : Percentage load of MCR (maximum continuous rating) of auxiliary engine for hoteling (Table 2) [5,38]. • HV: Heating value of fuel consumption (MJ/kg fuel). Considering marine gas oil as fuel, its value is 42.65 MJ/kg fuel [37] or 1 kg fuel/11.847 kWh. Trozzi and Vaccaro (Equations (9) and (10)) established two calculation methods based on GT. In addition to Ro–Ro ships, they also include passenger and cargo vessels, which means that they are not as specific as calculating power from GT. In the two final methods (Equations (11) and (12)), the auxiliary engine power is obtained from an estimation of the main engine power and an estimated average vessel ratio of auxiliary engines/main engines (AE/ME) by ship type, as described in the previous section. 2.3. Advantages and Disadvantages of Methods Initially, all methods need to take into account GT to calculate emissions. According to Table 2, only two calculation methods for the auxiliary engine power have all necessary values to obtain emissions (2010 World fleet and 2006 Mediterranean Sea fleet [5]). The AE/ME ratio or LFAE is not available for the other three methods. This problem would also affect the two methods used to calculate emissions from auxiliary engines’ fuel consumption (Schrooten [ 26 ] and Goldsworthy [ 44 ], and Fuentes García [ 32 ]), because they need to obtain the auxiliary engines’ power, and the 2010 World fleet method is applied to both cases. Nevertheless, the methods that calculate emissions from the estimated fuel consumption directly through the GT have no problem. In reference to engine emission factors for hoteling: • Emissions estimation methods from auxiliary engines’ fuel consumption include both marine diesel oil and marine gas oil. Marine diesel oil usually has a higher percentage of sulfur content than marine gas oil and therefore is more pollutant. Additionally, the CO2emission factor is not available for these methods; • Emissions estimation methods from auxiliary engines’ power use an emission factor adjusted to the fuel type “0.1% MGO” and comply with the limit of 0.1% sulfur content established by Directive (UE) 2016/802. 3. Application to Ro–Ro Ships in the Port of Vigo Below, the various methods described in the previous section and in Figure 1are applied to the specific case of Ro–Ro ships that have stopped in the Port of Vigo. The ultimate aim is to compare the methods and determine the most ideal calculation methodology. 3.1. Initial Data: Port Location and Ships under Study The Port of Vigo is located in the northwest of Spain, as shown in Figure 2. Being a port on the Atlantic Ocean makes it relevant for maritime routes. As far as goods shipping is concerned, the Ro–Ro lines stand out both at the European and transoceanic levels [ 23 ], as an important automotive company is also located in the city of Vigo. Moreover, the time Ro–Ro ships stayed in port was 9757 h for Vigo in 2018, compared to 606.5 h for transatlantic traffic—some 16 time higher [ 24 , 25 ]. For this reason, this study focused on Ro–Ro ship traffic in the Port of Vigo. J. Mar. Sci. Eng. 2023,11, 884 7 of 20 J. Mar. Sci. Eng. 2023, 11, x FOR PEER REVIEW 7 of 22 percentage of sulfur content than marine gas oil and therefore is more pollutant. Additionally, the CO2 emission factor is not available for these methods; • Emissions estimation methods from auxiliary engines power use an emission factor adjusted to the fuel type “0.1% MGO” and comply with the limit of 0.1% sulfur content established by Directive (UE) 2016/802. 3. Application to Ro–Ro Ships in the Port of Vigo Below, the various methods described in the previous section and in Figure 1 are applied to the specific case of Ro–Ro ships that have stopped in the Port of Vigo. The ultimate aim is to compare the methods and determine the most ideal calculation methodology. 3.1. Initial Data: Port Location and Ships under Study The Port of Vigo is located in the northwest of Spain, as shown in Figure 2. Being a port on the Atlantic Ocean makes it relevant for maritime routes. As far as goods shipping is concerned, the Ro–Ro lines stand out both at the European and transoceanic levels [23], as an important automotive company is also located in the city of Vigo. Moreover, the time Ro–Ro ships stayed in port was 9,757 h for Vigo in 2018, compared to 606.5 h for transatlantic traffic—some 16 time higher [24,25]. For this reason, this study focused on Ro–Ro ship traffic in the Port of Vigo. Figure 2. Ro–Ro terminal location in Port of Vigo. Source: Google Earth, 2020. The initial basis for this work is a Report of the Port Authority of Vigo (PAV), which included a viability study for the implementation of an onshore power supply (OPS) system, for application with the Ro–Ro ships that berth at the Port of Vigo [24]. The criteria followed in this report for the inclusion of ships were as follows (Table A2): • Minimum number of berthings per year: 10 (regular lines); • Minimum total stay time per year: 100 h; • Minimum stay time: 8.5 h (for the connection to be operational). To determine the methodology for calculating emissions, it was deemed ideal to define them for ships that berth in Vigo with some regularity and that have a relevant level of activity. For that reason, these criteria were adopted for the selection of ships. Because the data on berths from the PAV are from 2018, it was decided to update them by tracking Ro–Ro ships stopping in Vigo between July 2021 and March 2022, by means of open access information available from the MarineTraffic [45], VesselFinder [46] and vesseltracker.com [35] websites. This tracking detected three vessels that were out of service (Verona, Baltic Breeze and Arabian Breeze) and led to the addition of four more (Viking Amber, Viking Diamond, Mosel Ace and Prometheus Leader), which had berthed regularly during the tracking period and whose annual data could be estimated. Figure 2. Ro–Ro terminal location in Port of Vigo. Source: Google Earth, 2020. The initial basis for this work is a Report of the Port Authority of Vigo (PAV), which included a viability study for the implementation of an onshore power supply (OPS) system, for application with the Ro–Ro ships that berth at the Port of Vigo [ 24 ]. The criteria followed in this report for the inclusion of ships were as follows (Table A2): •Minimum number of berthings per year: 10 (regular lines); •Minimum total stay time per year: 100 h; •Minimum stay time: 8.5 h (for the connection to be operational). To determine the methodology for calculating emissions, it was deemed ideal to define them for ships that berth in Vigo with some regularity and that have a relevant level of activity. For that reason, these criteria were adopted for the selection of ships. Because the data on berths from the PAV are from 2018, it was decided to update them by tracking Ro–Ro ships stopping in Vigo between July 2021 and March 2022, by means of open access information available from the MarineTraffic [ 45 ], VesselFinder [ 46 ] and vesseltracker.com [35] websites. This tracking detected three vessels that were out of service (Verona, Baltic Breeze and Arabian Breeze) and led to the addition of four more (Viking Amber, Viking Diamond, Mosel Ace and Prometheus Leader), which had berthed regularly during the tracking period and whose annual data could be estimated. Starting from these considerations, the ships given in Table 9were selected. The table gives the corresponding characteristics that were used to establish the emissions estimation methodology. It shows that the interval for GT for the selected ships was approximately between 13,000 and 52,000 and for the annual hours spent berthing, between 105 and 2066 h. 3.2. Auxiliary Engines Power Estimate of Ro–Ro Ships From the GT data for each ship given in Table 9and the methods described in Table 2, the auxiliary engines’ nominal power was obtained (Table 10), taking the following aspects into account: • As the 1997 World fleet [ 5 ], Wang [ 27 ] and Oviedo UF [ 36 ] methods do not have an average ratio for auxiliary engines/main engines (AE/ME), the value of 0.24 (Table 2) was considered, which corresponds to 2010 World fleet [5]. • For the Wang [ 27 ] method, a load factor (LF AE ) of 0.4 was also considered, as it is not specified in the method (Table 2). Therefore, only the 2010 World fleet and 2006 Mediterranean Sea fleet methods have all the data needed to undertake the estimation of auxiliary engine power from the GT, as the AE/ME ratio and load factor (LF) are known (Table 2). That is why it is considered important to include the average value of the five methods, and the average value of 2010 World fleet–2006 Mediterranean Sea fleet as a reference range for errors when comparing the results and a criteria for selecting the estimation method to be used in this article (Table 10 and Figure 3). J. Mar. Sci. Eng. 2023,11, 884 8 of 20 Table 9. Ro–Ro ships selected and initial data. Ship Length (m) GT Year Built Flag No. of Annual Berths (Berths/Year) Hours per Year (h/Year) Average Time Spent in Berthing (h) Suar Vigo 140 16,361 2003 Spain 79 1601 20 Bouzas 149 15,224 2002 Spain 76 2066 27 Galicia 149 16,361 2003 Portugal 31 868 28 Tenerife Car 133 13,112 2002 Portugal 28 306 11 RCC Passion 168 36,834 2011 Bahamas 21 434 21 Coral Leader 176 40,986 2006 Bahamas 12 200 17 Emerald Leader 176 40,986 2008 Bahamas 12 167 14 Neptune Kefalonia 170 36,825 2009 Malta 12 105 9 Neptune Galene 170 37,602 2014 Greece 11 108 10 Opal Leader 176 40,986 2007 Bahamas 11 172 16 Vega Leader 180 51,496 2000 Panama 11 171 16 Victory Leader 186 49,675 2010 Bahamas 11 168 15 Viking Amber 167 39,362 2010 Singapore 28 474 17 Viking Diamond 167 39,362 2011 Singapore 33 283 9 Mosel Ace 176 37,237 2000 Liberia 24 244 10 Prometheus Leader 190 41,886 2008 Singapore 10 199 20 Table 10. Auxiliary engines’ consumed power (kW) estimate considering load factor of 0.4. Ship 2010 World Fleet (3) 1997 World Fleet (4) 2006 Mediterranean Sea Fleet (5) Wang (6) Oviedo UF (7) 5 Methods Average 2010/2006 Average Suar Vigo 1075.60 1041.25 1147.66 892.66 929.25 1017.29 1111.63 Bouzas 1042.42 998.04 1105.18 874.44 903.08 984.63 1073.80 Viking Diamond 1575.80 1745.55 1817.53 1147.74 1316.39 1520.60 1696.67 Galicia 1075.60 1041.25 1147.66 892.66 929.25 1017.29 1111.63 Tenerife Car 976.85 914.06 1022.03 837.84 851.13 920.38 999.44 Viking Amber 1575.80 1745.55 1817.53 1147.74 1316.39 1520.60 1696.67 Mosel Ace 1538.21 1689.46 1765.47 1129.65 1287.72 1482.10 1651.84 RCC Passion 1530.95 1678.67 1755.44 1126.14 1282.17 1474.67 1643.19 Coral Leader 1603.76 1787.58 1856.43 1161.10 1337.67 1549.31 1730.09 Emerald Leader 1603.76 1787.58 1856.43 1161.10 1337.67 1549.31 1730.09 Neptune Kefalonia 1530.79 1678.43 1755.21 1126.06 1282.05 1474.51 1643.00 Neptune Galene 1544.76 1699.18 1774.51 1132.81 1292.71 1488.79 1659.63 Opal Leader 1603.76 1787.58 1856.43 1161.10 1337.67 1549.31 1730.09 Vega Leader 1771.19 2044.59 2092.17 1239.52 1464.46 1722.39 1931.68 Victory Leader 1743.66 2001.73 2053.09 1226.81 1443.69 1693.80 1898.38 Prometheus Leader 1618.99 1810.57 1877.67 1168.35 1349.25 1564.96 1748.33 When considering the AE/ME ratio of 0.24 in the methods where these data were not available, the average obtained between 2010 World fleet and 2006 Mediterranean Sea fleet was 11% higher than the five methods’ average. Therefore, the procedure with results most in line with the established reference range was selected. From the results obtained, it was considered better to take into account the auxiliary engines’ nominal power calculated through the 2010 World fleet method for the following reasons: • Only in the 2010 World fleet and 2006 Mediterranean Sea fleet methods are all calculation data specified; J. Mar. Sci. Eng. 2023,11, 884 9 of 20 • The 2010 World fleet method covers a larger geographical area than the 2006 Mediterranean Sea fleet and is more in line with the location of the Port of Vigo as it is situated in the Atlantic Ocean; • Auxiliary engines’ power calculated with the 2010 World fleet method is usually within the reference range, while the 2006 Mediterranean Sea fleet figure is usually higher (Figure 3). J. Mar. Sci. Eng. 2023, 11, x FOR PEER REVIEW 9 of 22 Figure 3. Auxiliary engines consumed power (kW) in comparison with load factor of 0.4. When considering the AE/ME ratio of 0.24 in the methods where these data were not available, the average obtained between 2010 World fleet and 2006 Mediterranean Sea fleet was 11% higher than the five methods average. Therefore, the procedure with results most in line with the established reference range was selected. Table 10. Auxiliary engines consumed power (kW) estimate considering load factor of 0.4. Ship 2010 World Fleet (3) 1997 World Fleet (4) 2006 Mediterranean Sea Fleet (5) Wang (6) Oviedo UF (7) 5 Methods Average 2010 / 2006 Average Suar Vigo 1075.60 1041.25 1147.66 892.66 929.25 1017.29 1111.63 Bouzas 1042.42 998.04 1105.18 874.44 903.08 984.63 1073.80 Viking Diamond 1575.80 1745.55 1817.53 1147.74 1316.39 1520.60 1696.67 Galicia 1075.60 1041.25 1147.66 892.66 929.25 1017.29 1111.63 Tenerife Car 976.85 914.06 1022.03 837.84 851.13 920.38 999.44 Viking Amber 1575.80 1745.55 1817.53 1147.74 1316.39 1520.60 1696.67 Mosel Ace 1538.21 1689.46 1765.47 1129.65 1287.72 1482.10 1651.84 RCC Passion 1530.95 1678.67 1755.44 1126.14 1282.17 1474.67 1643.19 Coral Leader 1603.76 1787.58 1856.43 1161.10 1337.67 1549.31 1730.09 Emerald Leader 1603.76 1787.58 1856.43 1161.10 1337.67 1549.31 1730.09 Neptune Kefalonia 1530.79 1678.43 1755.21 1126.06 1282.05 1474.51 1643.00 Neptune Galene 1544.76 1699.18 1774.51 1132.81 1292.71 1488.79 1659.63 Opal Leader 1603.76 1787.58 1856.43 1161.10 1337.67 1549.31 1730.09 Vega Leader 1771.19 2044.59 2092.17 1239.52 1464.46 1722.39 1931.68 Victory Leader 1743.66 2001.73 2053.09 1226.81 1443.69 1693.80 1898.38 Prometheus Leader 1618.99 1810.57 1877.67 1168.35 1349.25 1564.96 1748.33 From the results obtained, it was considered better to take into account the auxiliary engines nominal power calculated through the 2010 World fleet method for the following reasons: • Only in the 2010 World fleet and 2006 Mediterranean Sea fleet methods are all calculation data specified; • The 2010 World fleet method covers a larger geographical area than the 2006 Mediterranean Sea fleet and is more in line with the location of the Port of Vigo as it is situated in the Atlantic Ocean; • Auxiliary engines power calculated with the 2010 World fleet method is usually within the reference range, while the 2006 Mediterranean Sea fleet figure is usually higher (Figure 3). Figure 3. Auxiliary engines’ consumed power (kW) in comparison with load factor of 0.4. 3.3. Auxiliary Engines Fuel Consumption Estimate of Ro–Ro Ships As already mentioned in the methodology section, there are two ways of estimating fuel consumption, either directly from GT or from auxiliary engines’ power, also obtained from GT. In the results shown in Table 11 and Figure 4, a difference of only 10% can be observed between the Trozzi and Vaccaro methods [ 28 – 34 ], probably due to the former being adjusted by means of linear regression, and the latter by a fourth-degree polynomial regression. However, there is a notable difference among the methods that calculate consumption from auxiliary engine power. The Schrooten [ 26 ] and Goldsworthy [ 44 ] methods take specific fuel consumption into account, and the Fuentes García method [ 32 ] considers the fuel heating value, representing only 30% of the consumption obtained by Schrooten [ 26 ] and Goldsworthy [44]. Table 11. Fuel consumption (kg/h) estimate comparison in port. Ship Method 1999—C. Trozzi and R. Vaccaro (9) Method 2006—C. Trozzi and R. Vaccaro (10) Schrooten and Goldsworthy (11) Fuentes García (12) Suar Vigo 319.64 411.31 233.40 90.79 Bouzas 304.86 384.50 226.21 87.99 Viking Diamond 618.66 609.15 341.95 133.01 Galicia 319.64 411.31 233.40 90.79 Tenerife Car 277.41 332.67 211.98 82.45 Viking Amber 618.66 609.15 341.95 133.01 Mosel Ace 591.03 619.24 333.79 129.84 RCC Passion 585.79 620.70 332.22 129.22 Coral Leader 639.77 599.26 348.02 135.37 Emerald Leader 639.77 599.26 348.02 135.37 Neptune Kefalonia 585.68 620.73 332.18 129.21 Neptune Galene 595.78 617.78 335.21 130.39 Opal Leader 639.77 599.26 348.02 135.37 Vega Leader 776.40 540.40 384.35 149.50 Victory Leader 752.73 544.41 378.38 147.18 Prometheus Leader 651.47 593.20 351.32 136.66 Total 8917.04 8712.32 5080.38 1542.81 J. Mar. Sci. Eng. 2023,11, 884 16 of 20 It is therefore proposed to estimate the emissions for each pollutant using Equation (17 ) and a factor, K, corresponding to each pollutant, by using Equation (36): EHoteling,i=(84.6219 +0.7075·Th,av)·N·Ki(36) As can be seen in Table 21, the difference between the two estimations is very small. Therefore, the proposed simplified estimation would be correct. Table 21. Emissions estimation results comparison by pollutant. Pollutant Emissions (t/Year) Equation (13) KiEquation (36) ∆Equations (13)–(36) (%) NOx107.27 0.015993 107.26 0.00271 PM10 1.80 0.000268 1.80 −0.10029 PM2.5 1.61 0.000240 1.61 −0.18818 SOx3.97 0.000592 3.97 −0.02915 CO26577.66 0.980742 6577.66 0.00007 VOC 3.78 0.000564 3.78 −0.06294 CO 10.40 0.001550 10.40 0.00157 N2O 0.27 0.000041 0.27 −0.33212 CH40.08 0.000011 0.07 2.42089 Total sum 6706.82 1.000000 6706.82 0.00001 A summary of the methods proposed in this article is given in Figure 7. J. Mar. Sci. Eng. 2023, 11, x FOR PEER REVIEW 18 of 22 Figure 7. Summary of proposed methods. This simplified method would be much faster and useful when making a first estimate of the total emissions from Ro–Ro ships in the Port of Vigo. It can perform both a global calculation, using the number of ships (N) that call at the port and the average hours of stay in hotels for all ships (T h,av ) (17), and per each pollutant (36), adding the corresponding factor (K i ) reflected in Table 21. 5. Conclusions This article has provided a bibliographical review of the existing methods for estimating the emissions of ships in port, depending on the power of their auxiliary engines and fuel consumption. As a result, the most relevant methods have been applied to the particular case of Ro–Ro ships in the Port of Vigo, which has allowed them to be compared. In both cases, since the power of the auxiliary engines and fuel consumption are unknown, these methods estimate them by means of regression curves, based on a characteristic parameter of the vessel such as gross tonnage (GT). Based on the analysis carried out, the best option selected in this article is the methodology for estimating emissions by means of auxiliary engine power according to 2010 World fleet [5] . From this methodology, the emissions of Ro–Ro ships during their stay in port are obtained on the basis of GT by using Equation (13). However, once the total emissions have been obtained, it can be seen that the weightiest parameter in the calculation is the number of hours for hoteling of a ship in port (T h ), instead of GT, and that the emissions increase as the number of hours increases (Figure 6). Consequently, a simplified estimation of total emissions from Ro–Ro ships during their stay in port was proposed, using the linear regression curve specified in Equation (17), as a function of the average value of hours for hoteling of ships in port (T h,av ) and number of ships (N). Furthermore, if an estimation is required for the different pollutant types, this article proposes Equation (36), which adds a K factor corresponding to each pollutant (Table 21). These equations are considered to be a potentially very useful and fast tool for obtaining the pollutant emissions of Ro–Ro ships during their stay in port. However, this article has some limitations. In the follow-up carried out on the 50 ships that called in the port between July 2021 and March 2022, only sixteen ships have had some regularity and a relevant level of activity according to criteria established in Section 3.1. Therefore, the procedure followed with Ro–Ro ships could also be applied to more Ro–Ro ships or other ship types, for which regression curves as a function of GT can also be found in the bibliography consulted and extrapolated for use in other ports. Another limitation is when auxiliary engine power or fuel consumption are not known. Although it is the basis of this article, it could also be interesting to compare the results obtained with real data. Author Contributions: Conceptualization, A.B.A.-L.; methodology, A.B.A.-L.; validation, A.B.A.-L.; formal analysis, A.B.A.-L.; investigation, A.B.A.-L.; data curation, A.B.A.-L.; writing—original draft preparation, A.B.A.-L.; writing—review and editing, C.C. and E.D.-D.; visualization, A.B.A.-L.; Figure 7. Summary of proposed methods. This simplified method would be much faster and useful when making a first estimate of the total emissions from Ro–Ro ships in the Port of Vigo. It can perform both a global calculation, using the number of ships (N) that call at the port and the average hours of stay in hotels for all ships (T h,av ) (17), and per each pollutant (36), adding the corresponding factor (Ki) reflected in Table 21. 5. Conclusions This article has provided a bibliographical review of the existing methods for estimating the emissions of ships in port, depending on the power of their auxiliary engines and fuel consumption. As a result, the most relevant methods have been applied to the particular case of Ro–Ro ships in the Port of Vigo, which has allowed them to be compared. In both cases, since the power of the auxiliary engines and fuel consumption are unknown, these methods estimate them by means of regression curves, based on a characteristic parameter of the vessel such as gross tonnage (GT). Based on the analysis carried out, the best option selected in this article is the methodology for estimating emissions by means of auxiliary engine power according to 2010 World fleet [ 5 ]. From this methodology, the emissions of Ro–Ro ships during their stay in port are obtained on the basis of GT by using Equation (13). J. Mar. Sci. Eng. 2023,11, 884 17 of 20 However, once the total emissions have been obtained, it can be seen that the weightiest parameter in the calculation is the number of hours for hoteling of a ship in port (T h ), instead of GT, and that the emissions increase as the number of hours increases (Figure 6). Consequently, a simplified estimation of total emissions from Ro–Ro ships during their stay in port was proposed, using the linear regression curve specified in Equation (17), as a function of the average value of hours for hoteling of ships in port (T h,av ) and number of ships (N). Furthermore, if an estimation is required for the different pollutant types, this article proposes Equation (36), which adds a Kfactor corresponding to each pollutant (Table 21). These equations are considered to be a potentially very useful and fast tool for obtaining the pollutant emissions of Ro–Ro ships during their stay in port. However, this article has some limitations. In the follow-up carried out on the 50 ships that called in the port between July 2021 and March 2022, only sixteen ships have had some regularity and a relevant level of activity according to criteria established in Section 3.1. Therefore, the procedure followed with Ro–Ro ships could also be applied to more Ro–Ro ships or other ship types, for which regression curves as a function of GT can also be found in the bibliography consulted and extrapolated for use in other ports. Another limitation is when auxiliary engine power or fuel consumption are not known. Although it is the basis of this article, it could also be interesting to compare the results obtained with real data. Author Contributions: Conceptualization, A.B.A.-L.; methodology, A.B.A.-L.; validation, A.B.A.-L. ; formal analysis, A.B.A.-L.; investigation, A.B.A.-L.; data curation, A.B.A.-L.; writing—original draft preparation, A.B.A.-L.; writing—review and editing, C.C. and E.D.-D.; visualization, A.B.A.-L.; supervision, C.C. and E.D.-D.; project administration, C.C.; funding acquisition, C.C. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Ministry of Science and Innovation (Spain) under the project “Integración de la energía fotovoltaica flotante marina en la costa atlántica (grant number PID2021-127876OB-I00)”. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest. Appendix A Appendix A.1. Information about Marine Diesel Engines Generally speaking, marine diesel engines can be classified according to their speed [ 36 ]: •Slow-speed engines: below 300 rpm and two-stroke. These offer propulsion with the lowest specific consumption. They tend to use high-viscosity fuel oil; • Medium-speed engines: between 300 and 1000 rpm and four-stroke. These offer propulsion and power generation using fuel oil, marine diesel oil, or even marine gas oil; • Fast-speed engines: over 1000 rpm and four-stroke. These are used as generators or in small ships for propulsion. They tend to use marine gas oil. According to ENTEC 2010 [ 37 ], auxiliary engines are mainly medium-speed (58%), with the rest being fast-speed (42%). Moreover, the USA EPA 2009 study [ 4 ] on the methodologies to use when calculating the emissions of marine transport also states that when no data are available on the speed of an auxiliary engine, it can be considered to be medium-speed. The tier of an engine is a reference to the nitrogen oxides emissions limit according to Annex VI of the MARPOL Convention, according to the engine speed (Table A1). J. Mar. Sci. Eng. 2023,11, 884 18 of 20 Table A1. Revised Annex VI of MARPOL Convention—NO x emission limit (n-rated engine speed in rpm). Tier Date NOxEmission Limit (g/kWh) n< 130 130 ≤n< 2000 n≥2000 Tier 0 1990–1999 17.0 45·n−0.2 9.8 Tier 1 2000–2010 17.0 45·n−0.2 9.8 Tier 2 2011–2015 14.4 44·n−0.23 7.7 Tier 3 ≥2016 3.4 9·n−0.2 1.96 Appendix A.2. Information about Ro–Ro Ships Selected in the PAV Report Below are the characteristics of the Ro–Ro ships selected in the PAV Report [ 24 ], which stopped in the Port of Vigo in 2018 (Table A2). Table A2. Ro–Ro ships selected in the PAV Report [24]. Ship Length (m) GT Annual Berths Hours per Year Average Time Spent in Berthing (h) SUAR VIGO 140 16,361 79 1601 20.27 BOUZAS 149 15,224 76 2066 27.19 GALICIA 149 16,361 31 868 28.01 TENERIFE CAR 133 13,112 28 306 10.91 ARABIAN BREEZE 164 29,874 23 411 17.86 RCC PASSION 168 36,834 21 434 20.66 VERONA 177 37,237 18 263 14.63 BALTIC BREEZE 164 29,979 17 337 19.84 CORAL LEADER 176 40,986 12 200 16.64 EMERALD LEADER 176 40,986 12 167 13.95 NEPTUNE KELAFONIA 170 36,825 12 105 8.72 NEPTUNE GALENE 170 37,602 11 108 9.85 OPAL LEADER 176 40,986 11 172 15.64 VEGA LEADER 180 51,496 11 171 15.55 VICTORY LEADER 186 49,675 11 168 15.31 References 1. State Ports. Guide to Energy Management in Ports; State Ports: Madrid, Spain, 2012; p. 296. (In Spanish) 2. Yigit, K.; Acarkan, B. A new electrical energy management approach for ships using mixed energy sources to ensure sustainable port cities. Sustain. Cities Soc. 2018,40, 126–135. [CrossRef] 3. 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Available online: https://www.vesselfinder.com/ (accessed on 28 March 2022). Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.