Existing Emission Calculation Methods Applied to Monitoring, Reporting and Verifi cation (MRV) on Board

Monitoring, Reporting and Verifi cation (MRV) of emissions on board has been proposed as a measure to reduce global greenhouse gas (GHG) emissions. The requirements for MRV are set by two legislative bodies, the European Union (EU-MRV) and the International Maritime Organization (IMO-DCS) and ships have to comply with them. However, current maritime practices do not permit the right implementation of MRV and best practices can only be developed after a certain time of experience. A solution could be the application of the diff erent existing emission calculation methods on the phase of MRV where it is most useful. This contribution explores which method could be useful as maritime best practices and could meet the goals of EU-MRV and IMO-DCS. Eleven existing methods have been assessed by a set of questions based on key MRV elements found in literature. Methods have been classifi ed within Theoretical Based Methods (TBM) and Ship Based Methods (SBM). TBM methods may not comply with the monitoring phase of MRV but could be feasible as alternative method when activity data from ships are extracted. On the other hand, SBM methods seem to be the most appropriates to comply with MRV specifi cations, but need more investments on board and therefore require best practices regarding the way of application. The assessed methods are already available, possibly suitable to be used for monitoring, and therefore applicable as early best practices, with the understanding that some of the methods are theoretical, based on assumptions, and often too general. Nevertheless, a diff erent approach like the one presented in this contribution may be supportive in the understanding of MRV on board.


INTRODUCTION / Uvod
Maritime transport is a contributor to global warming and air pollution. The total shipping fuel consumption increased from 291 to 298 million tonnes from 2013 to 2015, increasing the emissions over this period, including CO 2 , CH 4 , and N 2 O emissions [1]. Moreover, shipping is responsible for 15% and 13% of global NO X and SO X emissions respectively in 2012 [2]. Shipping global greenhouse gas (GHG) emissions are increasing despite improvements in operational effi ciency for many ship types. Various measures and methods are proposed to reduce the environmental impact of shipping: (i) slow steaming [3,4], (ii) the use of alternative fuels like hydrogen or Liquefi ed Natural Gas (LNG) [5] and (iii) technical and design optimizations [6,7,8]. Other measures like the obligatory Energy Effi ciency Design Index (EEDI) -improving ship effi ciency by ship design -and the voluntarily Energy Effi ciency Operational Index (EEOI)improving effi ciency by operational measures -are introduced to stimulate shipping to become more effi cient [9]. [10] argue that eff ective energy management is incompa tible with established shipping business practices. An energy effi ciency gap is recognized due to the existence of barriers [11,12]. Some examples of these hampering barriers are: (i) lack of reliable information about the reduction potential of effi ciency measures, (ii) lack or a perceived lack of technical information, (iii) costs issues, (iv) organizational structures and (v) inconsistent legislation [11,13,14,15]. Moreover, best practices related on energy consumption monitoring require real-time disaggregated data for each consumer (or at least the main consumers). In this sense, Monitoring, Reporting and Verifi cation (MRV) emissions on board has been proposed as a measure to reduce GHG [16]. Therefore, the annual fuel consumption and/or carbon emissions of each individual ship needs to be reported to the legal authorities and the results are verifi ed assessing if ships comply with the regulations or if some actions need to be taken in the future. The requirements for MRV are set by two legislative bodies, the European Union (EU-MRV) [17] and the International Maritime Organization (IMO-DCS, Data Collection Scheme) [18]. On one hand, annual reported emission data should be made transparent by making these publicly accessible proposing four methods for monitoring on board: (1) using bunker fuel delivery note (BDN), (2) bunker fuel tank monitoring, (3) Flow meters for applicable combustion processes and (4) Direct CO 2 emissions measurements. On the other hand, the Marine Environmental Protection Committee (MEPC) of IMO agreed on a global MRV scheme and results obtained should be stored in the IMO Ship Fuel Oil Consumption Database and should be analysed and used as benchmark for new regulations. Table 1 shows the diff erences and similarities between both regulations.
Both regulations emphasize that the extra (administrative) burden on the crew should be as low as possible, prioritizing the use of the existing systems in monitoring to keep extra investments as low as possible. This is the reason why the European scheme proposes two methods that are already available for ships: the use of bunker delivery notes and fuel tank soundings; the other two methods require additional investments. However, shipping faces uncertainty about the way of monitoring: which parameters need to be measured and which data is required and how? Paradoxically, analogue problems arise around the implementation of MRV. [10] concludes that current maritime business practices do not permit the right implementation of MRV. What is required and how to implement and apply MRV on board ships?
Existing practices are not well developed and shipping has already to comply with both regulations being crucial to fi nd suitable methods for MRV. The main objective of this paper is to assess the existing methods for inventorying ship emissions and to fi nd best practices that will help the correct implementation of MRV. Therefore, this contribution is organized as follows: after the Introduction (Section 1), the key essentials of MRV (such as quality, uncertainty and confi dence) are provided in Section 2. Section 3 (methods) presents an overview of the existing methods for calculating ship emissions (including the four proposed by EU-MRV) and a set of MRV related questions. Section 4 shows the results after the assessment of these methods in order to conclude which of them are possibly suitable for MRV or useful for some phase of MRV. Finally, discussion and conclusions are highlighted in fi nal sections (Section 5 and Section 6 respectively).

MRV KEY ESSENTIALS LITERATURE / Osnove MRV-a u literaturi
Emission reduction goals cannot be reached when a method for Monitoring, Reporting and Verifi cation emissions does not meet the fundamental requirements. These fundamentals need to be clear before a method is assessed for its usefulness. [19] present a list of elements that should be included in an MRV scheme used

Quality / Kvaliteta
The quality of the application and outcome of an MRV program is an important issue. Quality assurance is essential for the confi dence in the program and the integrity of the work done. Equipment performance standards, competency of personnel and strong auditing methods are included in good quality assurance [19]. The monitoring equipment needs to be trustworthy and reliable. Reliable monitoring needs skilled people who are involved in the monitoring process such as the monitoring operators and reporters and also auditors in the validation process. It is important that all actors/stakeholders do what is expected of them within the MRV scheme. Training and understanding is of vital importance. Therefore, a collaborative approach in the process is meaningful. There is a constant interaction among the legislating, executing, and controlling actors. Collaboration provides a better compliance rate, resource savings, understanding and a more productive relationship among the actors. [20] highlight the human role for the implementation of energy effi ciency measures in the maritime domain. According [21] -as cited by [20] -many shipping companies do not possess the ability to address energy effi ciency measures on a systematic base within their organisations. One of the main causes of this lack of ability is that shore operations and ship operations are often confronted instead of aligned in their way of working. This issue hampers the implementation of MRV on board. Quality is strongly related to the validity of MRV because it should improve the monitoring results.

Uncertainty / Nedoumica
Uncertainties are inherent to monitoring, caused by the lack of accuracy and precision in the measurement process [16]. Quality control and verifi cation can be used to deal with the lack of accuracy and precision. Systematic errors can only be reduced by monitoring and reporting the same parameter by diff erent methods. The sensitivity analysis shows if the monitoring method is consistent between observation and expectation or observation and requirement [22]. There are two important trade-off s concerning uncertainty and reliability of the results: (i) information relevance versus comparability and (ii) cost versus uncertainty [16]. On one hand, one can monitor data, which is only relevant to a certain ship type, but then this data might not be comparable with other types of ships. If the data is comparable, the monitored data might lose relevance. On the other hand, the costs of a MRV system might be high when one desires to reduce uncertainties in the monitoring process to a minimum. This also implies that low-cost monitoring systems are aff ected by higher levels of uncertainty. According to [16] the principles and concepts of an MRV scheme are often proposed without signifi cant attention to how such schemes are applied in practise in relation with uncertainty. Not many MRV schemes set requirements concerning uncertainty in monitoring and how to deal with them. EU-MRV [17] states that levels of uncertainty correspond with the requirements, national regulations, costumer contracts, and/or fuel suppliers' norms.
Regulations require ships larger than 5,000 GT to take part in MRV; other ships are regarded as less signifi cant for the total emission amount. The monitoring inventory needs to be as complete as possible [18]. The example of relevance in MRV is which sources to include and which not [19]. For instance, the EU-MRV lists the sources of emission on-board for which fuel and emissions must be monitored and reported: main engines, auxiliary engines, boilers, turbines and inert gas generators (for tankers only). Consequently, other emissions sources, such as incinerators, do not necessarily need to be reported. The inventory may be valid without low emitting sources. Assumptions or emission factors might be used to substitute real measured data for low emitting or unknown sources. Non-reliable emission factors or estimated emission factors may increase the uncertainty or errors in the results [23].

Confi dence / Povjerenje
General confi dence in the program is achieved by making the data publicly available for the sake of transparency. Available data is absolutely required for letting the market do its work to achieve effi ciency improvements at the lowest costs. Public data gives access to valuable information to maritime community stakeholders in order to be able to analyse it and invites all actors involved to discuss, alterate and improve the program.

METHODS / Metode
This paper focuses on the assessment of the existing emissions methodologies inventory and analyses their impact on MRV right implementation on behalf of quality, uncertainty and confi dence elements. The applied methodology consisted of a description of eleven existing methods used for making ship emissions inventories including the four methods proposed by EU-MRV. Then, with the data gathered, each method is grouped into (i) Ship Based Methods (SBM) or (ii) Theoretical Based Methods (TBM). SBM focus on the collection of data on board of each individual ship. On the other hand, TBM's emission results are (partly) obtained via modelling, and there is no or a limited amount of data recorded on board. Subsequently, a list of six questions is developed based on the above section theory to assess the usability of these methods for MRV on board: Q1. Which data is monitored and which required data is assumed? Q2. How is data collected? Q3. Which human competency is required? Q4. How are the trade-off s dealt with in terms of information and costs? Q5. What are the main uncertainties within the method and how are they dealt with? Q6. Will the MRV goal be met with the method?
The fi rst two questions are general questions about how and what data is collected. The fi rst fi ve questions are based on [16], which deal with the trade-off s. The last question assesses whether the method can meet the goals from EU-MRV and IMO-DCS or not. These questions are used in the following section to assess the methods for their MRV relevance and fi nd the method or methods which fi t best in MRV application stages.

Emission Calculation Methodologies (ECM) inventory / Popis metodologija za izračun emisija
Eleven existing methods for fuel consumption and emission determination are considered, namely: ENTEC UK Limited [24]; Ship Traffi c Emissions Assessment Model and latest versions (STEAM) [25,26]; methods for estimating shipping emissions in the Netherlands (TNO) [27]; the California Air Resources Board (CARB) method [28]; Use of questionnaires method [29]; On board monitoring devices [30]; Use of Portable Emissions Measurement Systems (PEMS) [31,32]; Flow meters for applicable combustion processes; Continuous Emissions Measurements (CEM); Bunker fuel tank monitoring [33] and Bunker Fuel Delivery Note (BDN) [34]. All methods are described briefl y below: 1. ENTEC UK Limited (TBM): The overall objective of this method is to make preliminary assignments of ship emissions to European countries such as sulphur dioxide (SO 2 ), nitrogen oxides (NO X ), volatile organic compounds (VOCs), particulate matter (PM) and carbon dioxide (CO 2 ), for the years 2000, 2010, 2015 and 2020. Seven diff erent methods are applied to assign emissions. The assignment methods to be investigated are a selection of "top-down" and "bottom-up" approaches. 5. Use of questionnaires (TBM): This method uses questionnaires to obtain emission from ships in port, analogue to CARB but from a more generalist point of view. The questionnaire contains questions about general ships characteristics such as ships name, type, volume, year of construction, IMO number (to access more detailed ship data on a later moment). Furthermore, the questionnaire asks for fuel consumption at diff erent stages of shipping: cruising at open sea, manoeuvring towards harbour and while at berth together with duration of stay at berth. Simultaneously, fuel quality and the type of engine and/or machinery in which the fuel is used are requested. The method aims to cover the full spectrum of ship types as well as ships volumes and succeeds rather well at this by covering a wide range of ships volumes for most current ship types.
6. On Board Monitoring Devices, OBMD (SBM): This method is based on the monitoring devices that vessels have on board: Global Positioning System (GPS) and engines fuel consumption meters. The voyage fuel consumption can be calculated in various scenarios of speeds and weather conditions, so the GPS speed data of the ship could approximate the ship's fuel consumption. When the consumption data is combined with measurements of actual speed and position (based on GPS signals) it is possible to directly measure the fuel effi ciency. The second device, engines fuel consumption meters, is based on measured fuel fl ows on board for a specifi c period. The fuel type and the sulphur content need to be monitored. 7 9. Flow meters for applicable combustion processes (SBM): This method is founded on measured fuel fl ows on board. The data from all fl ow meters linked to relevant CO 2 emission sources can be combined to determine total fuel consumption for a specifi c period. The period means the time between two port calls or time within a port. For the fuel used during a period, the fuel type and the sulphur content need to be monitored. The calibration methods applied and the uncertainty associated with fl ow meters used shall be specifi ed in the monitoring plan. 10. Bunker Fuel Tank monitoring on board, BFT (SBM): This method is based on fuel tank readings for all fuel tanks on board. The tank readings shall occur daily when the ship is at sea and each time the ship is bunkering or de-bunkering. The cumulative variations of the fuel tank level between two readings constitute the fuel consumed over the period. Fuel tank readings shall be carried out by appropriate methods such as automated systems, sounding and dip tapes. The method for tank sounding and uncertainty associated shall be specifi ed in the monitoring plan.
11. Bunker Fuel Delivery Note, BDN (SBM): BDN contains information that may be used for the monitoring of fuel consumption in a certain time period and therefore to estimate CO 2 emissions. The accuracy of BDN data varies depending on how the fuel quantity stated on the BDN is determined. BDNs have an accuracy level of 1 to 5% and they can provide an insight into the absolute amount of fuel consumed in a specifi c period of time when combined with a stock-take at the beginning and at the end of the time period under consideration. This monitoring approach can therefore be used for time-based policy measures and direct incentive for emissions reductions.

RESULTS / Rezultati
This section provides the results of the assessment of all the emission calculation methodologies for MRV relevance explained in the above section. The following tables (from Table 2 to Table   Table 2  7) compare all these methods considering the list of questions formulated in order to enable the choice of one (or more) of them depending on their suitability.   The model includes many stages and, during the stages, information is gathered. At first glance the method tries to be as complete as possible by combining other methods. The eff ort in time for the collection of data, emission calculation and evaluation of the results are the main costs.

STEAM
An inclusive method which takes many parameters into account. The model also tries to be as complete as possible. The collection of data and following steps are assumed to take some eff ort and are thus costly.

TNO
A method with a high assumption rate to present a certain order of magnitude of PM emissions. Only collection of basic data required. Not assumed to be very costly.

CARB
Results are subtracted from survey information which is held on board. The aim of the method is clearly defined and not extensive. The collection during the survey takes some time and it is the stage in the method with the highest costs. However it is not assumed to be very high.

Questionnaire
A simpler approach to determine ship emissions, due to a lack of essential technical data. Elemental parameters have to be assumed. The method tries to be complete, but some results may present an order of magnitude due the assumptions that have been made. It takes some eff ort to collect the data by the questionnaire and the modelling takes some time as well.
OBMD Information and costs depend on the aim of which the devices are used for. Require investment, running, and maintenance costs. Costs will be higher when using more monitoring devices.

PEMS
The price can vary greatly depending on the quality and accuracy of the device. Application of the device needs to be done according to the prescribed standards and it may cost some time.

CEM
Requires investment and running costs; requires higher maintenance. Price can vary greatly depending on the quality and accuracy of the devices.  ENTEC Based on the derived function and the estimated uncertainties of the input parameters the uncertainty of the preliminary emission results is estimated. Depending on the methodologies proposed by ENTEC, uncertainties range is from 10 to 42%.

STEAM
Significant uncertainties exist in determining the time spent at sea, engine load profiles used and emission factors applied. Uncertainties regarding the chemical composition and other properties of the emitted PM. Uncertainties regarding the emission factors of NO X . The change of emission factor due to engine load is not taken into account. Uncertainties concerning the predicted power of the auxiliary engines, which significantly aff ect the emissions in port areas. The way to deal with these uncertainties is getting as much data as possible.

TNO
A theoretical calculation method based on AIS and LR Data. There are some assumptions made. The information relevance is not sensitive as there is no fuel consumption rate shared and it is applicable to any type of vessel as long as technical data is available. Uncertainty estimates for greenhouse gas emissions have been quantified in referenced report. Due to a lack of technical data, emissions are presented as a function of gross tonnage instead of using the more accurate g/kWh. The former is namely a linear relation and does not take into account the economy of scale. Depending on methodology used (Tier) and compound analysed, uncertainties could go from 3% up to 50%.

CARB
Emissions calculation method is not explained. All requested information was given and was kept confidential; data can be compared but not for all types of vessels.

Questionnaire
All requested information was given and kept confidential; data can be compared but not for all types of vessels. Uncertainty is high in some cases. Correlation coeff icients are rather low and the variability in the outcome was rather large. For three ship types the correlation is poor (Container ships, General Cargo and "Other"). OBMD Depending on way of measuring.

PEMS
It is often diff icult for PEMS to off er the same accuracy and variety of species measured as it is possible with top of the line laboratory instrumentation. The uncertainties depend on the quality and accuracy of the device. CEM Uncertainties range is +/-2%.

Flow-meters
Highest potential accuracy.
BFT Sensitive to inaccuracies as it relies only on fuel tank readings. Discrepancies between the tank volume calculated and the actual volume consumed due to on board fuel treatment processes. BDN Uncertainties range is from 1 to 5%. They vary depending on how the fuel quantity is determined.
The fi rst fi ve methods are Theoretical Based Methods (TBM) and the last six are Ship Based Methods (SBM). As it arises from above tables, some TBM methods do not comply with the monitoring phase of MRV as they take the technical data for emissions calculation from databases (such as Lloyd Register) and not from real-time variables measured on board.
Nevertheless, the assessment also shows that some TBM's could be feasible as alternative methods when using questionnaires to extract activity data from ships. Approaches such as STEAM or CARB are excellent methods to verify the monitoring phase. In addition, some TBM might be used for verifi cation in terms of comparing the results obtained from the data recorded on board with modelling outputs. For instance, ENTEC and STEAM are based on ship movement information for individual ships instead of generalising as per ship type or Gross Tonnage range. STEAM verifi es ship emissions by modelling the ship's work based on AIS, technical data and real-time weather and sea conditions. Furthermore, it also considers the nowadays existing emission abatement techniques. In terms of the importance of the waves for individual ships, the estimated increase of hourly fuel consumption could be between 10-20% [25]. Further hourly averaged and voyage specifi c fuel consumption data is needed to draw more detailed conclusions regarding the signifi cance of the eff ect of waves. On a local scale or for individual ships, the eff ect of waves is not necessarily negligible. Furthermore, STEAM points out for being the method with most realistic outputs when comparing them to real data. Much of the uncertainty of the TBM methodologies in the activity data for shipping emission estimates is related to the diffi culty of distinguishing between national and international fuel consumption (from ±5% to ±50%). Reporting is expected to improve the global data sets which may be helpful in this area as stated by ENTEC. On the other hand, SBM methods seem to be the most appropriates to comply with MRV specifi cations. Even though, there are some nuances to take into consideration. The SBM which use on board monitoring equipment are feasible when the output is considered. The potential of these methods lies on the monitoring process used. Firstly, one can monitor the fuel consumption and carbon content of the exhaust gasses; the basic approach to comply with regulations. Secondly, ships can monitor other additional (relevant energy) processes or proxies by implementing more measuring and monitoring equipment. Accordingly, more processes can be followed. In addition, when taking into account SBM as BDN, for instance, it is widely known that there exists some reluctance to divulge this information to a third party. Furthermore, when focusing on board monitoring devices or fuel meters, all recirculated fuel should be taken into account. When talking about PEMS or CEM, besides the costs implied, there has to be a system installed on every stack, the system must be continuously working, all monitored data correctly documented and reported, the equipment requires frequent calibration and this has to be done by experienced operators. Aforementioned statements mean more investment. SBM could give realistic values on emissions depending on the methodology analysed, as for PEMS or CEM, for instance. However, these 2 methodologies will not mandatorily discriminate the source neither. It would be desirable to mount an independent fl ow meter for each fuel consumer in order to be able to discriminate the consumption and to obtain distinctive and reliable emissions data.

DISCUSSION / Rasprava
The shipping industry has practically no other choice than to implement MRV on board because the measures are already ratifi ed and legally binding. It is important that the companies defi ne, in the monitoring plan, which monitoring methodology is used to calculate fuel consumption for each ship type under its responsibility and must ensure that once it has been chosen, is consistently applied. However, some aspects of MRV can be problematic and the success of best practices depends on how the shipping industry perceives MRV on board their ships. Their main issues are qualitatively summed up as follows: 1. The data that needs to be collected is rather sensitive and needs to be treated as confi dential. The results may

STEAM
Taking into account that accuracy in terms of fuel consumption is 6%, when comparing results from STEAM theoretical approach to information given by ship owners, it could be concluded that this approach could be used for emissions estimation, provided all requested data were available. Furthermore, method outputs could be compared with real values in MRV verification phase.

TNO
As this methodology does not include the direct measurement of gas concentration neither the record of proxies, it might not meet all MRV goals but it is a good method for estimating emissions and for using the method outputs afterwards in the verification phase comparing real values with modelling outputs. aff ect the economic or legal position of ship owners [36]. Additionally, there is the problem of who is responsible for the fuel consumption and resulting emissions in time charters. The charterer of a vessel is responsible for the fuel input (supply and payments) during time charters and the charterer might be the party who has the primary MRV responsibility [37]. 2. The shipping industry demanded anonymity of their data in the future MRV schemes during negotiations for the new MRV legislation. In IMO-DCS, anonymity is ensured in the assessment of the submitted data. The discussion of anonymity generates tension between public interest and economical interest.

CARB
3. Uncertainty about the way of monitoring: which parameters need to be measured and which data is required, and how, what to do with the data, what to say about the quality of the data and what about the extra costs? [15] 4. A major issue is the diff erence between EU-MRV and IMO-DCS (see Table 1). Ships have to comply with both schemes but they demand diff erent input and diff erent administrative management [38], which in view of the shipping industry needs extra work to reach the same goal in two ways. This situation hampers the idea of 'low extra administrative burden' and is most probably not supportive for the three issues above.
5. An important issue would be the amount of diff erent pollutants emitted into the atmosphere and this could be analysed by the methodologies proposed. Nevertheless, when talking in terms of emissions mitigation, distinctive data should be obtained in order to apply correct procedures for each consumer.
Based on the above explanation, the arguments are mostly practical; paraphrased as: what do we need to do and what are our gains? This study does not answer these questions directly, but hopes to present a diff erent point of view, so that the industry picks up the gauntlet and starts to develop its so-needed best practices. The methods -especially STEAMcould be used in the verifi cation process analogue to the ATC verifi cation in aviation, because of the use of AIS data. [39] verifi ed the results from IMO's Third GHG Study [2] with aid of the STEAM approach and both results agreed. But what would happen if an approach like the one used in STEAM is used the other way around, so that the monitoring is performed via modelling? Monitoring is shifted from ship to shore and ship owners only have to verify the results. Starting with such a way of monitoring would be the development of a best practise without the direct involvement of the shipping industry. A third party scrutinizes the movements of the vehicles and calculates the emissions. If the results are in a same order of magnitude, the modelling results will be published and available to the market. Data about fuel consumption and emissions will be collected without direct eff orts of ship operators. [39] argue that the STEAM models are quite suitable to "analyse emission results in a detailed and versatile manner" and can perfectly be used on smaller scale, because the model is applicable onto individual ship level.

CONCLUSION / Zaključak
Current maritime business practices do not permit the right implementation of Monitoring, Reporting and Verifi cation. Best practices are required as knowledge base for a complete and correct application of MRV. However, best practices can only be developed after a certain time of experience and ships have to comply with the European Union (EU-MRV) and the International Maritime Organization (IMO-DCS) regulations. A sol ution could be the application of existing theoretical approaches which are able to determine ship emissions on individual ship level. This research is one of the fi rst attempts to evaluate the existing emission calculation methods to be used for energy and emission monitoring on board ships and could be useful for the maritime business. Eleven existing methods have been assessed by a set of MRV related questions based on key MRV elements (quality, uncertainty and confi dence) found in literature. Methods have been classifi ed as Theoretical Based Methods (TBM) and Ship Based Methods (SBM). When taking a look into TBM it could be concluded that these methodologies are more generalist. Most of the TBM off er the possibility to calculate emissions from the values of the emission factors published. Others, as STEAM, give the possibility to calculate the emission factors theoretically based on the fuel portion of Carbon and Sulphur or based on IMO regulations for NOx. Taking this information into account, the theoretical emissions could be calculated as far as the fuel consumption is known but this will not discriminate among diff erent sources of emissions unless fuel consumption data for each engine or boiler on board is available. TBM methods may not comply with the monitoring phase of MRV but could be feasible as alternative method when using real-time data to extract activity data from ships. Moreover, some TBM methods might be used for verifi cation in terms of comparing the results obtained from the data recorded on board with modelling outputs (for instance ENTEC and STEAM). The STEAM method deter mines ship emissions by modelling the ship's work based on AIS, technical data and real-time weather and sea conditions, while it also considers abatement techniques. Therefore, STEAM points out as being the methodology with the most realistic outputs when comparing with real data. STEAM could be suitable to use as a diff erent approach for MRV, but this method has not been tested as early best practices. On th e other hand, SBM methods seem to be the most appropriates to comply with MRV specifi cations. Nevertheless, some of the SBM methods require more investment. In this contribution, a diff erent approach is presented and existing methods could be applicable as early best practices on Monitoring, Verifi cation and Reporting emissions on board.