Mass-Balance Method for Provision of Net Zero Emission Transport Services

Abstract

There is a strong need to reduce emissions from transport and logistics. Electrification and use of greener energy carriers and fuels provide a ready way to reduce emissions, but these technologies are generally more expensive than the conventional ones they are replacing. Fortunately, some shippers are willing to pay the extra cost to ship their goods using net zero emission transport solutions. To capture this demand, carriers need to decarbonize a part of their operations related to the transport volumes of the “green” shippers. This paper proposes a mass-balancing method based on carbon footprinting to equip the carriers with a verifiable way to market net zero emission services without creation of operational inefficiencies and physical separation of conventional and low emission transport. The paper shows feasibility and rather “easy” data requirements of the method in an application case on real world data of a deep-sea carrier.

1. Introduction

There is a strong need to reduce emissions and decarbonize transport and logistics. The International Transport Forum estimates that 30% of all transport emissions are coming from international freight transport, representing 7% of all global emissions [1]. On the ITS projections, these emissions could grow by a factor 3.9 in 2050. On the policy side, in the realization of the Paris agreement, the European Commission (EC) proposes to target a 55% reduction of greenhouse gas (GHG) emissions by 2030 compared to the 1990 level [2]. Specifically for the transport sector, the EC proposes by 2030, as a decarbonization means, to increase the renewable share to around 24% through further development and deployment of electric vehicles, advanced biofuels and other renewable and low-carbon fuels as part of a holistic and integrated approach [3]. All transport sectors, including inland and maritime waterborne transport, will have to contribute to the 55% reduction effort through a combination of vessels efficiency improvements, fuel mix changes and more sustainable energy sources.

Several technical solutions exist or are in development to reduce transport emissions without the need to completely re-organize transport systems. These range from replacing conventional (diesel) fleet of vessels or road vehicles by electric ones, or by the use of greener/green fuels and energy carriers, such as biofuels and synthetic fuels. These technologically ready solutions provide a relatively quick way to reduce transport emissions, but they come at a higher cost and may not yet be scalable due to insufficient short- to medium-term production volumes. In addition to the high capital investments, transport companies also face higher operational expenditures when switching to greener solutions. At this moment, conventional transport solutions that are based on the use of fossil fuels are cheaper in the out-of-pocket terms. The cost of fossil hydrogen ranges between $1 and $4/kg, whereas that of e-hydrogen currently ranges between $6 and $8/kg, the cost of green methanol at $643/tonne or $0.032/MJ and fossil methanol at $417/tonne or $0.021/MJ [4]. For road transport, although there is some optimism for the development of electric trucks [5], long haul operation of electric trucks presents a substantial challenge due to the costs, range and payload limitations compared to the diesel vehicles [6].

There is a widely accepted need to increase and improve decarbonization efforts in transport and logistics in a verifiable and monitorable way. On the basis of a systematic literature review of system dynamics models in relation to strategies for freight decarbonization, Ghisolfi et al. (2022) [7] draw the conclusion that freight transport decarbonization is currently an urgent challenge. Davydenko et al. (2019) [8] argue that carbon footprinting provides insights into emissions and the activities that cause them, and thus carbon footprinting (CF) provides one of the most important instruments for decarbonization. Wild (2021) [9] suggests standardization of carbon footprinting at the global level with the goal of harmonization and comparability of the computations. Introduction of CF procedures almost always results in unexpected findings of reduction potential [10]. Davydenko et al. (2014) and Davydenko et al. (2020) [11,12] provide methodological foundations for the carbon footprinting methods. The CF methods are being standardized now: the ISO 14083 working group has started the process of international standardization, which is planned to be completed at the end of 2022. Besides allocation of emission to customers’ shipments, the carbon footprinting methods look very promising for allocation of the costs related to the Emission Trading System (ETS). As part of the Fit for 55 work program [2], a proposal was made to extend ETS to maritime transport, and a separate legislation will be set up for road transport. Because it is expected that the carriers will, as much as possible, pass on ETS-related costs to their clients, a solid and widely accepted methodology is needed for allocation of these costs to the customers. Figure 1 presents conceptually the principles of carbon footprinting using a simple fictive example. One of the main goals of carbon footprinting is to determine and allocate of GHG emissions realized by the carrier(s) proportionally to transport activity of the clients, expressed in tonne-kilometres (tkm) or tonne-(nautical) miles, on whose behalf these activities (and corresponding emissions) have been realized. In the example of Figure 1, the total amount of 5 kg CO₂ in the carrier network is allocated to the two shippers proportionally to their transport activity: 40% (=20/50 tkm) is allocated to Shipper 1 and 60% (=30/50 tkm) to Shipper 2.

Luckily, there is evidence that some shippers are considering using green logistics solutions for their transport needs [12]. Shippers focus more on sustainability than forwarders, and the size of shippers has a positive influence on the demand for transparency of the environmental performance [13]. Their explicit sustainability targets have a positive influence on the demand for sustainable solutions, and the vast majority of shippers and forwarders expect an increased importance of sustainable [14].

The ‘green’ shippers want to decarbonize their operations, including those of third parties that they hire to do, among other, transport work. Decarbonization strategies may be very beneficial from purely business considerations, such as market image and reduction in the costs of capital. Due to the fact that these companies do not represent the majority of shippers yet, to capture demand for zero (or low) emission transport products, transport service providers face essentially a choice to do one of the following:

• decarbonize operations at own cost; or
• create a sub-set of zero/low emission operations for dedicated clients who pay the premium costs; or
• do nothing and not serve the ‘green’ shippers.

These three options are sub-optimal because it either (1) makes carrier operations unsustainably expensive, (2) creates operational inefficiencies of segmented operations, or (3) is unacceptable given the goals of decarbonization.

The scientific novelty of this paper is in presentation of a CO₂ mass-balance method that allows carriers to offer zero emission or low-carbon solutions to those shippers who are willing to pay a premium for such products. This method is new and simple to implement and understand by the logistics service providers and the users of transport, who will be able to show real emission reductions related to their transport. It can be seen as a fourth option in the list of options above. Figure 2 presents a simple example that illustrates the concept of mass balancing: Shipper 1 orders 20 tkm of zero emission transport that is realized somewhere in the carrier’s network, and not necessarily by physically transporting these zero emission volumes of Shipper 1. However, by paying for the net zero transport volumes, Shipper 1 ensures that the carrier only emits 3 kg instead of 5 kg CO₂, which would be the case without the request by Shipper 1 to transport her volumes in a zero-emission way. The realized reduction of CO₂-emissions will be at least as much as would have been attributed to Shipper 1 if its shipments were carried out in a conventional way (see Figure 1).

Implementing the CO₂ mass-balance method essentially creates an additional implementation strategy for transport companies in which they can efficiently capture paying demand for low or zero carbon solutions and not damage carriers’ operational efficiency. This method allows mixing of conventional and low-carbon operations to avoid unnecessary segmentation of operations, while ensuring to the shippers who pay for zero emission or low-carbon transport solutions that their transport volumes are served by the bought services and do not contribute to emissions of greenhouse gasses. In other words, the method provides for separation of operations and emission accountancy ensuring that paid-for volumes of zero emission transport are carried out without emissions in the carrier’s transport system.

It is important to underscore that, physically, the volumes for the net zero customers would not necessarily travel on zero or low emission vehicles. The developed method provides a means for third party accountants, who can certify compliance, and hence allow shippers who buy the premium low or zero emission transport solutions to include the results of their decarbonization efforts in their own reports (e.g., corporate sustainability reports, input to ESG scores, etc.).

The paper is structured in the following way. Section 2 provides a concise literature review building upon earlier efforts on development of carbon footprinting methods and arguing that extra costs of decarbonization on the part of (large) shippers may be offset by reduction of the capital costs. Section 3 provides a formal specification of the mass balancing method, including mathematical specifications. The method has been applied on real world data of a carrier. Section 4 provides an account for how the method can be used to determine the necessary volumes of low-carbon transport and how to keep administration for the audit. Section 5 provides a discussion on applicability and limitations of the developed mass-balance method. The conclusions are drawn in Section 6 together with an outline for further research.

2. Literature Review

A number of technical solutions exist to reduce transport emissions without the need to completely re-organize transport systems. These range, for instance, from replacing conventional (diesel) trucks by electric ones, to the use of greener/green fuels and energy carriers, such as biofuels and synthetic fuels in maritime vessels [15,16]. Financing these solutions is difficult, especially for carriers that have a large fleet (of trucks or ships) and that can only gradually implement innovations. These carriers, furthermore, often serve a large set of shippers, of which only some are willing to pay a premium for low-carbon transport. A challenge lies in how carriers can efficiently use carbon friendly transport solutions in their networks while insetting (emission insetting in this context means a company offsetting its carbon emissions within its own transport chain; note that emission offsetting means a company offsetting its carbon emissions elsewhere, not necessarily within its own transport chain) the achieved CO₂-savings to clients who specifically pay for carbon-friendly transport [17].

There is ongoing research on the reduction of maritime emissions and the role of E-fuels in this process [18], as E-fuels are a promising technological input solution for the mass balancing method application in practice. On the side of ports, operational energy balancing strategies such as power sharing, load shifting and peak shaving may result in improvements of the energy efficiency and environmental performance of ports and terminals [19]. There is a substantial literature body on optimization and choice techniques to improve transport performance [20,21]; this paper goes beyond transport flow optimization and discusses a solution that can work in parallel with the optimization techniques, amplifying their effectiveness.

A potential method to achieve this is via CO₂ mass balancing. The basic idea of a mass-balance method is that a certain amount of decarbonization effort is realized in a network of a carrier, and that the benefits of decarbonization are accrued to the shippers that pay for this decarbonization, while physically the decarbonization may not take place in the exact part of the network that serves these paying customers. To our knowledge, there is no formal definition of a mass-balance method for CO₂ balancing in transport networks and provision of truly zero emission transport solutions on the basis of low-carbon transport. Smart Freight Centre (2020) [22] stated that a method for CO₂ insetting, as a form of mass balancing, is required in logistic networks. A high level of transparency and auditability is needed for such a method to gain traction: knowledge, trust and credibility are antecedents of carbon offsetting behavior [23]. Zhang et al. (2019) [24] come to the same conclusion in the context of voluntary carbon offsetting products to encourage consumers to mitigate emissions from their air travel. In the context of airline offsetting schemes, the adoption of alternative biofuels and Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) implementation are necessary steps towards a carbon neutral future in aviation [25]. For the transport modes, where batteries are not an option in the foreseeable future, the adoption of alternative biofuels and CORSIA-like implementations are necessary steps towards a carbon neutral future.

The idea of mass balancing outside the realm of transport decarbonization is not new. It already has been used to account for fair mixing of sustainable and unsustainable shares in products as fuels or biomass, as well as in food products such as sustainable palm oil [26]. The mass-balance methodology allows the physical mix of sustainable and nonsustainable products on every stage of the value chain. Although the product loses its individual properties, the balance of quantities is fully traceable throughout the whole supply chain. The specific properties of sustainable material are determined via bookkeeping. This requires calculation and frequent monitoring of the mass-balance calculation [27]. Mass balancing requires a well-thought implementation of gain sharing of collaborative efforts among shippers [28], where extra costs on the part of one organization can be compensated by the gains realized in the system. Inclusion of external costs, such as the costs of CO₂ pollution, may influence the modal split and amount of emissions for the goods flows, e.g., Comi and Polimeni (2020) [29].

There is a body of financial and economic research showing that the efforts to improve ESG (environment, social and governance) scores reduce the cost of (equity) capital. ESG metrics enable investment advisory firms to create broad-based or “targeted” funds that focus on general or specific environmental/social/governance screens, such as a company’s level of carbon emissions relative to its industry peers [30]. A higher ESG score increases inflow of the capital from investors who appreciate efforts to reduce emissions, among other things. Investing in companies with a high ESG score comes at a cost to the investor [31] through lower costs of borrowing and increased valuations, which favor incumbent investors. Conversely, participation in “sin” industries increases firms’ cost of equity, underscoring that firms with socially responsible practices have higher valuation and lower risk [32]. These ideas have found support and empirical evidence in the financial industry: ESG scores influence the cost capital (both of equity and debt). A study by MSCI [33] has found that the difference in cost of capital can exceed 0.5% between low ESG and high ESG companies across companies from the developed markets (USA, Europe and Japan). This implies that businesses may be willing to bear higher transport costs of low-carbon and zero-emission transport if it reduces the costs of capital and increases shareholder returns. This is an important consideration because it decreases the need of voluntary do-good efforts and shift decarbonization efforts into the realm of return maximization.

A mass-balance method requires insights into performance of the transport networks with respect to CO₂ emissions. Carbon footprinting is a good method to obtain this data. Carbon footprinting analyses GHG emissions and attributes these emissions to the activities that cause them. Carbon footprinting provides the decarbonization process with the data on actual emissions (ex-post) and expected emissions (ex-ante) related to the proposed improvements. References [7,8,10,34,35,36,37,38] provide reasoning and technical specifications on how carbon footprinting can be realized in practice.

Some first steps in application of carbon footprinting methods for development of a mass-balance method have been made by Engelenhoven (2021) [39], in which the concept of credits is used to balance low-carbon transport sold to shippers on the one hand with real-world emission reduction in the carrier network on the other hand. It provides potentially a feasible and certifiable direct mass-balance method for allocation of green credits to the customers. However, this method only works with low-carbon transport solutions that still emit GHG, and the method does not envisage true zero emission transport solutions that can be verifiably developed using carbon footprinting. Engelenhoven (2021) [40] concludes that a mass-balance method is relevant because it can boost green transport in the logistics sector, ensure that customers are more willing to pay, cover the extra costs, and boost the idea of carbon insetting.

The basic idea behind mass-balance methodology is that the market needs to be segmented. There are shippers who do not want to pay a premium for zero or low-carbon transport, and there are shippers who are willing to pay for it (“green shippers”). If a carrier does not provide zero emission transport solutions, the carrier can potentially miss demand from ‘green’ shippers; on the other hand, a carrier who applied carbon reduction methods may capture demand from the green shippers but will not be paid a premium by the other shippers. Because the margins of carriers are generally small (EBIT margins generally range from −1% to 8%, [40]), carbon reduction measures cannot be made reliably profitable in current market conditions if only a part of the customers cover the cost. The mass balancing (see Figure 2) provides a way to segment transport products for different customers without segmenting operations, thus avoiding inefficiencies of fractured transport operations.

Segmentation enables a seller to treat the customers relevantly according to their characteristics. In this way, the seller can satisfy more of its customers by meeting more customers’ needs and wants, and the seller can also use the most appropriate methods in marketing to serve them more effectively [41]. In support of this idea, Ref. [42] show that there is a relationship between market segmentation and carbon performance: an increased market potential can support improved carbon performance. For market segmentation to drive profits, a company must identify the customer groups that matter to the company’s financial performance [43]. For CO₂ mass balancing in logistics, there should be distinguished customer groups that can be clearly identified as conventional customers and customers who want to pay extra for CO₂-reduced transport. As Seitz et al. (2015) [44] note, carriers are hesitant to adopt new low CO₂ emission solutions because they expect that in the future it will be less expensive. The segmentation of products allows carriers to buy low emission solutions now, as there is paid demand on the part of “green shippers”, and not to wait until it becomes cheap.

3. Mass-Balance Method for Low Carbon and Zero Emission Solutions

We propose the mass-balance method to be based on carbon footprinting of transport operations [7,8,10]. Carbon footprinting (CF) is an important tool for reduction in CO₂ and other GHG emissions from freight transport and logistics [45]. A properly implemented CF procedure provides for visibility of carbon emissions in supply and logistics chains, thus creating opportunities to understand reduction potentials and implement emission reduction measures. The implementation of CF procedures, as well as the mass-balance methodology, requires data collection to perform the calculations. The mass-balance methodology is described in the following section. The methodology is applied in a practical application case in Section 4.

Formal Definition of Mass Balancing Methodology

Carbon footprinting can be seen as an analysis of GHG emissions and attribution of these emissions to the activities that cause them. In its very basic form, carbon footprinting determines GHG intensity of operations, which is expressed in kilograms of CO₂-equivalent per tonne-kilometre (or tonne-nautical mile in maritime shipping) transported. The carbon footprinting convention for transport and logistics requires that the CO₂-equivalents are expressed in Well-to-Wheel (WTW) emissions [46,47]. The WTW emissions include not only the direct emissions of burning fuels (e.g., so-called tailpipe emissions), but also emissions related to production, transport and distribution of the fuels. For certain fuels, such as biofuels, the production phase may involve negative emissions, when biomaterial is built by carbon taken out from the atmosphere.

Suppose within a certain uniform Transport Operation Category (TOC, a group of transport operations that share similar characteristics) that a certain amount of transport activity T measured in tonne-kilometeres (tkm) is carried out. While carrying out transport activity T, the carrier emits E kilogram of CO₂-equivalent GHG emissions. The relative performance of the TOC is carbon intensity I expressed in kgCO_2eq/tkm. I is computed as

$$I=\frac{E}{T}$$

(1)

It is obvious that the lower emission E, the lower is the carbon intensity of transport operations. In case of zero emission transport, the carbon intensity (emissions per tonne-kilometre) I is also zero. A general recommendation of the GLEC Framework and the future ISO 14083 standard is to aggregate TOC operations over a year such that the effects of seasonality climate-wise and demand-wise are smoothed out; in justifiable cases, the time aggregation can be smaller down to individual trips.

If a shipper sends a shipment S via the TOC with network intensity I, the carbon footprint (emissions) related to the shipment can be determined as

$$E_S=I T_S$$

(2)

$$T_S=W_S D_S$$

(3)

where T_S is the tonne-kilometre transport activity associated with shipment S. Transport activity related to shipment S is determined as the weight of shipment S (W_S) multiplied by the distance D_S over which shipment S is transported within the TOC (Equation (3)). Recent research [48] shows that the Great Circle Distance metric is the most suitable distance metric for determining the transport activity because it is immutable and can be determined by the locations where the shipment is loaded onto a vehicle and the locations where it is offloaded, while the knowledge on the routing is not necessary. Figure 3 uses the example of Figure 1 to visualize Equations (1) and (2).

The total transport activity of the TOC is the sum of the transport activities of all shipments within the TOC; likewise, the total emissions of the TOC is the sum of all shipment-related emissions.

$$T={{\displaystyle \sum }}^{ }{T}_S$$

(4)

$$E={{\displaystyle \sum }}^{ }{E}_S$$

(5)

The Equations (4) and (5) may seem trivial, but they have an important function: all transport activity and emissions within the TOC should be accounted for and allocated. This includes emissions related to empty kilometres that are necessary to relocate assets for the next shipment.

Suppose further that within a TOC, two types of transport means are used: conventional and low carbon. Conventional transport means are, for example diesel trucks, diesel vessels, fossil-fuel-driven deep-sea vessels or airplanes powered by kerosene-based jet fuel. Examples of low-carbon transport are electric trucks, hydrogen trucks or vehicles of all modalities driven by biofuels or synthetic fuels. The general characteristic of the low-carbon transport means is that they emit much less CO₂ per unit of transport activity than the conventional transport means but cannot be considered as zero-emission transport means. For instance, burning bio-diesel fuels releases 9 to 56 g CO₂ per GJ (Well-To-Wheel/Wake) depending on the used feedstock, where burning bio-methanol from a waste feedstock can release as low as 5 to 8 g CO₂ per GJ [49]. The same applies for the electrically driven vehicles; they do not emit any GHG in operation, but currently production of electricity does emit CO₂.

$$E=E^C+E^L$$

(6)

$$T=T^C+T^L$$

(7)

Equation (6) postulates that the total TOC emissions E is the sum of emissions released by conventional transport means within the TOC E^C and emissions released by low-carbon transport means E^L. Likewise, the TOC’s transport activity is the sum of transport activity by conventional and low-carbon transport means (Equation (7)). There could be more types of transport means (e.g., electric, HVO, green hydrogen or green methanol), which can be distinguished as different types of low-carbon solutions. However, for the sake of simplicity, we make a distinction between only two types of transport means: conventional (C) and low carbon (L). This leads to two different carbon intensities within the same TOC:

$$I^C=\frac{E^C}{T^C}$$

(8)

$$I^L=\frac{E^L}{T^L}$$

(9)

The mass-balance methodology provides a way to separate the operation from the administration. This also implies that the products that are sold to shippers (‘administration’) can be different from the technologies that are used in real-world transport (‘operation’). A carrier may offer a zero-emission transport product to the shipper by showing in ‘administrative’ terms that the transport volumes of the shipper are carried out in a net zero emission way. Because there are no truly zero-emission (WTW) transport means on the market, zero emission transport has to be carried out by low-carbon transport means in the operation. As low-carbon transport still emits GHG emissions, for the quantity of zero emission transport volumes sold T^Z, there should be carried out more transport volumes by low-carbon transport T^L, and these volumes must not be sold as low-carbon transport to other shippers. With the two products ‘conventional’ and ‘net zero’ transport, it is possible to sell a whole range of lower-carbon products. For example, if a shipper wants to buy transport that emits 30% less CO_2eq-emissions, this can be seen as an equivalent to buying 70% of the conventional product and 30% of the net zero product for its requested transport activity.

Table 1. Overview of two transport options in the operation and two products in the administration.

Operation	Administration
Option 1: Conventional transport with carbon intensity IC	Product 1: conventional
Option 2: Low carbon transport with carbon intensity IL	Product 2: net zero

provides an overview of the two products in the administration and the two technologies in the operation.

The main requirement of the mass-balance methodology is that all emissions resulted from operations are accounted for in the administrative part. In other words, a carrier has to account for all real-world emissions in the administration. To be able to sell a certain amount of net zero emission transport volumes (i.e., net zero tonne-kilometres), it is important to shift the right amount of transport activity to the low emission transport solutions, namely by shifting transport volumes from T^C to T^L (Equations (8) and (9)). The relation between the amount of net zero transport activity sold (T^Z) and the amount of low-carbon transport activity in the operation (T^L) is defined in the mass-balance Equations (10) and (11).

$$Mass balance formula, transport demand side: T^L\ge T^Z\frac{I^C}{I^C-I^L}$$

(10)

$$Mass balance formula, transport supply side: T^Z\le T^L\frac{I^C-I^L}{I^C}$$

(11)

The mass balance has two formulations. Equation (10) specifies the minimum amount of low-carbon transport activity that is needed to satisfy customer demand for net zero carbon transport. It is demand driven on the part of shippers. Equation (11) specifies the upper limit of how much net zero transport can be sold given the carrier capacity to realize low-carbon transport. This is a supply-driven formulation that is useful to assess the potential volume of net zero emission transport that can be sold in case a carrier introduces a new low-carbon transport solution (e.g., electric vehicles, methanol ship).

The demand-driven mass-balance Equation (10) is based on the fact that Equation (1) can be rewritten. Suppose further that in this formulation, the numerator E is the total amount of CO_2eq emissions that needs to be reduced in the network of the carrier to sell T^Z amount of net zero transport activity, in which the denominator is the amount of CO_2eq emissions that will be reduced by shifting one unit of transport activity from the conventional network with carbon intensity I^C towards the low-carbon network with carbon intensity I^L. This leads to a minimum amount of transport activity specified by Equation (10) that needs to be shifted from the conventional network towards the low-carbon network. Note that both T^Z and T^L can consist of shipments for multiple shippers and are in that case the sum of the transport activities for respectively all net zero and all low-carbon shipments and related transport activity.

Note the factor in Equation (10) between the net zero transport activity in the administration T^Z and the low-carbon transport activity in the operation T^L. It is referred to as the mass-balance factor. Under all realistic conditions, the mass-balance factor is larger than 1, and the amount of low-carbon transport volumes T^L that are necessary to carry out will always be larger than the amount of sold net zero emission volumes T^Z.

$$Mass balance factor: \frac{I^C}{I^C-I^L}$$

(12)

In addition to the mass-balance Equations (10)–(12), there are two other requirements. The first requirement is that the new low-carbon volumes created to satisfy net zero demand cannot be larger than existing volumes of conventional transport that they displace (i.e., the emission reduction takes place within the transport network of the carrier). The second requirement is the qualitative condition that the low-carbon transport volumes $T^L$ that are used for provision of net zero transport $T^Z$ are not sold in other green products such as low-carbon transport. Figure 4 provides an illustration of a mass-balance application using low-carbon technology to achieve net zero transport for a shipper.

4. Practical Application Case

The mass-balance methodology described in Section 3 has been applied in an application case with a carrier—Wagenborg. The case shows a practical applicability of the method emphasizing its feasibility and relative ease of implementation in the operations of a carrier. The carrier has kindly provided the authors with the data to analyze applicability and usability of the described in Section 3 mass-balance methodology.

4.1. Case Description

The carrier manages a multipurpose fleet of 170+ dry cargo vessels of which 80 vessels are owned by the carrier. To optimize the network, the majority of vessels in the fleet are not dedicated to specific customers but are assigned to shipments based on their characteristics and their position in the network. Depending on the transport demand, the carrier’s fleet performs 10 to 150 journeys for a typical customer per year. The data presented in this application case is real-world data for a subfleet of 24 vessels during one year (2020).

As shown in Table 1, there are two customer products that customers can buy: conventional and net zero emission. A range of emission reduction subproducts can potentially be specified by mixing only these two products. On the operation side, transport is presumed to be carried out in a conventional way or by using low-carbon technology that is available to the carrier or will become available in the coming years. The three transport options on the operation side are described below.

1.

Conventional transport: gasoil.

Conventional transport is carried out by using a mixture of Low Sulfur Fuel Oil and Marine Gas Oil. For this application case, we aggregate these two fuels into one conventional fuel using weighted average of the carbon content of each of the fuels. The carbon intensity of the conventional transport network is obtained by dividing fuel-related emissions by the transport activity carried out within the boundaries of the TOC.

2.

Low carbon technology 1: gasoil bio-fuel blend with 30% Hydrated Vegetable Oil (HVO).

Blending a fossil fuel with a 30% bio-component does not directly lead to a 30% reduction in GHG emissions. Two factors influence the effective CO₂-reduction: (1) HVO has a smaller carbon footprint, which is 1.681 gCO₂/g fuel (WTW) instead of 3.579 gCO₂/g fuel for the conventional fuel mix (LSFO); (2) HVO has a slightly higher energy content, which is 44 MJ/kg fuel instead of 40.6 MJ/kg fuel for LSFO. Low carbon technology 1 (a 30% HVO blend) will therefore reduce the net CO₂ (WTW) by roughly 15.9% for the same amount of transport activity, see

Table 2. Relative calculation of relative CO₂ emissions per unit of energy for 30% HVO blend and bio-methanol. Sources: [50,51].

	gCO2/g Fuel WTW	MJ/kg Fuel	gCO2/MJ WTW (LSFO = 100%)
Conventional: LSFO	3.597	40.6	88.6
			(100%)
Fuel to blend: HVO	1.826	44.0	41.5
Low carbon technology 1: 30% HVO and 70% LSFO	3.099	41.6	74.5
			(−15.9%)
Low carbon technology 2: Bio-methanol	0.152	23	6.60
			(−93%)

.

3.

Low carbon technology 2: retrofit vessel from gasoil to bio-methanol from waste material.

The second low-carbon technology that is considered in the application case is retrofitting of a conventional vessel into a bio-green methanol vessel. The fuel properties determine the effective CO₂-reduction per unit of transport activity. Bio-methanol based on black liquor has a 97% reduction in mt CO₂/mt fuel (WTW [50], compared to conventional fuel. Because the energy content (in terms of MJ/mt fuel) of green methanol is lower than that of the conventional fuel, it requires a 117% increase in fuel use weight-wise. This results in an effective CO₂-reduction of 93% (gCO₂/MJ) for the same amount of transport activity, see Table 2. Note that these assumptions on reduction do not include the differences in fuel efficiency per engine type and are only based on difference in energy-density per weight and emitted CO₂ in fuel production and dual distribution chains.

Due to maritime legislation, the mass-balance method application does not require collection of new data in operations of maritime carriers. The data that are used in the application case have already been collected by the carrier due to existing maritime policies in Europe (EU-MRV). The (EU-MRV) regulation makes the implementations of the method easy for the operation of ships with gross tonnage of 5000 gt for which the European regulation apply. Both two main data elements, which are required for carbon footprinting and mass balancing application, transport activity (in tonne-nautical miles) and CO₂-emission (in tonnes), are required to satisfy reporting conditions of this regulation and, thus, do not need to be collected apart.

The total amount of transport activity is the sum of transport activity per shipment. The transport activity of a shipment is the weight (in tonnes) multiplied by the distance (in kilometres or nautical miles for the shipping). The total amount of CO₂-emissions is equal to the sum of CO₂-emissions per fuel type, and the CO₂-emissions of a fuel type are equal to the amount of fuel used (in tonnes) multiplied by the WTW emission factor of that fuel (in tonne CO₂/tonne fuel). Figure 5 provides an overview of the application case baseline, which includes the transport activity, the WTW CO₂-emissions and the carbon intensity of the considered transport network. We select a shipper (“Shipper 1”) to show its transport activity in relation to all other shippers within the TOC, as these activity data are used in one of the mass-balance scenarios.

Table 3. Carbon intensities for conventional, two options of low carbon and net zero transport.

	$\mathbf{Conventional} {\mathit{I}}^{\mathit{C}}$	$\mathbf{Low} \mathbf{Carbon} {\mathit{I}}^{\mathit{L}}$ 30% Bio-Blend	$\mathbf{Low} \mathbf{Carbon} {\mathit{I}}^{\mathit{L}}$ Green Methanol	$\mathbf{Net} \mathbf{Zero} {\mathit{I}}^{\mathit{Z}}$
Carbon Intensity [gCO2/tnm]	20	16.8	1.5	0

and

Table 4. Carbon intensities for conventional, two options of low carbon and net zero transport.

Method Type	Step 1	Step 2	Example
Demand-driven	Use the shipper demand for net zero transport to fill the administration side of the mass balance.	Use the mass-balance formulation to fill the operation side of the mass balance based on the administration in step 1.	Scenario 1
Supply-driven	Use the carrier supply of low-carbon transport to fill the operation side of the mass balance.	Use the mass-balance formula to fill the administration side of the mass balance based on the operation in step 1.	Scenario 2 and 3

present an overview of the different carbon intensities that are used in the case. The conventional carbon intensity is based on the data in the baseline, and the carbon intensities for the two low-carbon options are based on the effective CO₂-reduction percentages as described in Table 2: 15.9% for a 30% bio-blend and 93% for green methanol. The application case is based on the real-world data; the numbers are adjusted and rounded to make it easier to understand the essence of the calculations.

The application case considers three scenarios in which the mass-balance methodology is applied:

• In scenario 1, the shipper wants to reduce its emissions by 60%. This reduction can be realized by buying 60% of net zero transport and 40% of the conventional transport for its transport volumes. The carrier applies conventional transport and low-carbon technology 1 (30% HVO blend). The question is how much transport activity needs to be shifted from conventional to the low-carbon part of the fleet.
• In scenario 2, the carrier only applies low-carbon technology 1 (30% HVO blend) to the entire fleet. The question is, what is the maximum amount of net zero transport that can be sold?
• In scenario 3, the carrier retrofits one vessel with low-carbon technology 2 (green methanol). The question is what the maximum amount of net zero transport is that can be sold.

The results of the three scenarios are presented in Section 4.2.

4.2. Mass-Balance Method Application Results

In general, the mass-balancing methodology can be applied from the transport demand side (Equation (10)) and from the transport supply side (Equation (11)) point of view. This can be seen from the carrier’s perspective as demand-driven (customer-driven) or supply-driven (technology-driven). In a demand-driven scenario, a shipper has demand for net zero transport, and the question is how much of a certain low-carbon technology has to be realized on the operation side to fulfill this demand such that, administration-wise, the shipper attains its net zero emission transport. In a supply-driven scenario, a carrier has a certain supply of low-carbon transport on the operation side, and the question is, what is the maximum amount of net zero transport that can be sold on the administration side? Table 4 summarizes the steps to take in a mass-balance scenario for the two method types: demand-driven and supply-driven.

The following two subsections illustrate possible implementations for the mass balancing methodology for both demand-driven and supply-driven approaches. As we expect that real-world applications of the mass balancing methodology would require verification and approval by the accountants or third-party auditors, we present computations in a form that is easy to understand from the accountancy point of view, making it less abstract, by distinguishing the administration part and operation parts. In practice, other ways of implementation exist; the authors do not insist on this way of implementation.

4.2.1. Scenario 1: Sell Net Zero Transport to Shipper 1 by Using a Bio-Fuel Blend as Low Carbon Technology

The first scenario is an example of a demand-driven method application. ‘Shipper 1’ intends to buy net zero CO₂ transport for 60% of its shipments. The question to be answered using the mass-balance methodology is how much transport activity the carrier needs to shift from conventional to the low-carbon part of the network to ensure the required reduction of CO₂-emissions. The low-carbon technology that is used in this scenario is a 30% HVO blend. Because this technology is not zero-emission, it is necessary to shift more transport activity to the low-carbon technology than the net zero transport activity demanded by ‘Shipper 1’. This scenario assumes that all other shippers keep buying the conventional transport product.

The first step in a customer-based scenario is to determine the quantity of net zero emission transport required by Shipper 1. It can be done by filling in the administration side of the mass balance, see

Table 5. The administration side of the mass balance in Scenario 1.

	Administration
	Transport Activity [109 tnm]		CO2 [kton]
Scenario 1	Conventional	Net Zero	Total
Shipper 1	0.04	0.06	0.8
Other shippers	9.9	-	198.0
Total shippers	9.94	$\mathbf{0.06} (T^Z)$	198.8

. Shipper 1 wants to buy a mix of 60% net zero transport and 40% conventional transport. The corresponding CO₂-emissions are based on the carbon intensities from Table 4 for conventional transport ($I^C=200/10=20 {\mathrm{gCO}}_2/\mathrm{tnm}$) and net zero transport ($I^Z=0{ \mathrm{gCO}}_2/\mathrm{tnm}$), and the CO₂-emissions for Shipper 1 are 0.8 kton CO₂ (=0.04 × 20 + 0.06 × 0), see

Table 6. The operation and the administration side of the mass balance in Scenario 1.

	Operation			Administration
	Transport Activity [109 tnm]		CO2 [kton]	CO2 [kton]	Transport Activity [109 tnm]
Scenario 1	Conventional	Low Carbon	Total	Total	Conventional	Net Zero
Shipper 1	0.10	-	2.0	0.8	0.04	0.06
Other shippers	9.5	0.38	196.8	198.0	9.9	-
Total shippers	9.6	$\mathbf{0.38} (T^L)$	198.8	198.8	9.94	$\mathbf{0.06} (T^Z)$

.

The second step in a demand-driven scenario is to fill the operation side of the mass balance based on the mass-balance formulation in inequality (10). This formula uses the carbon intensities of $I^L=16.8 {\mathrm{gCO}}_2/\mathrm{tnm}$ and $I^C=20.0 {\mathrm{gCO}}_2/\mathrm{tnm}$ (see Table 3). The amount of low-carbon transport activity that is required on the operation side to meet the customer demand of 60% net zero transport on the administration side is demonstrated as follows:

$$T^L\ge T^Z\frac{I^C}{I^C-I^L}=0.06\times \frac{20}{20-16.8}\cong 0.38$$

(13)

In this scenario, the minimum amount of transport activity that needs to be executed with the low-carbon technology (30% HVO bio-blend) is 0.38 × 10⁹ tnm to ensure 0.06 × 10⁹ tnm net zero transport activity for Shipper 1. In this scenario, there is enough conventional transport volumes available to be shifted to low-carbon operations. It is up to the carrier in which part of the fleet the low-carbon technology is applied, and this does not necessarily have to cover the actual shipments for Shipper 1. In this example the low-carbon transport activity is executed physically for other shippers than Shipper 1, which results in the mass balance as presented in

Table 7. The operation side of the mass balance in Scenario 2.

	Operation
	Transport Activity [109 tnm]		CO2 [kton]
Scenario 2	Conventional	Low Carbon	Total
Total shippers	-	$10.0 (T^Z)$	168

, in which the purple cell denotes the outcome of the mass-balance estimation of the minimum requirements for low-carbon transport. Note the difference between the operational and the administrative CO₂-emissions per shipper, but the total CO₂-emissions in the network of the carrier are the same on both sides of the mass balance (green box). The important message of Table 7 is that in order to preserve operational efficiency, the low-carbon volumes are not necessarily realized in operations of shippers’ who bought them, but the carrier must ensure that they are realized somewhere in its TOC.

4.2.2. Scenario 2: Maximum Amount of Net Zero Transport by Using a Bio-Fuel Blend as Low Carbon Technology

The second scenario is a supply-driven scenario in which the carrier applies a low-carbon technology to its entire fleet. The question to be answered using the mass-balance methodology is, what is the maximum amount of net zero transport activity that the carrier can sell to its customers? The low-carbon technology that is used in this scenario is a 30% HVO blend. As in Scenario 1, because this technology is not zero-emission, the amount of net zero transport activity that can be sold is lower than the total transport activity in the network.

The first step in a supply-driven scenario is to determine the volume of low-carbon transport activity on the operation side. This can be done by filling in the operation side sheet of the mass balance, see

Table 8. The operation and the administration side of the mass balance in Scenario 2.

	Operation			Administration
	Transport Activity [109 tnm]		CO2 [kton]	CO2 [kton]	Transport Activity [109 tnm]
Scenario 2	Conventional	Low Carbon	Total	Total	Conventional	Net Zero
Total shippers	-	$10.0 (T^L)$	168	168	8.4	$1.6 (T^Z)$

. All transport activity is performed by the low-carbon technology, and this technology has a carbon intensity of $I^L=16.8 {\mathrm{gCO}}_2/\mathrm{tnm}$ (see Table 3).

The second step in a supply-driven scenario is to fill the administration side of the mass balance based on the mass-balance inequality (11). This formulation uses the carbon intensity of the low-carbon technology 30% bio-blend, which can be found in Table 4. The maximum amount of net zero transport activity that can be sold on the administration side based on the low-carbon transport on the operation side is demonstrated as follows:

$$T^L\ge T^Z\frac{I^C}{I^C-I^L}=0.06\times \frac{20}{20-16.8}\cong 0.38$$

(14)

In this scenario, the maximum amount of net zero transport activity that can be sold is 1.6 × 10⁹ tnm with an amount of 10 × 10⁹ tnm of low-carbon (30% HVO bio-blend) transport activity in the operation. This results in the mass balance as presented in

Table 9. The operation side of the mass balance in Scenario 3.

	Operation
	Transport Activity [109 tnm]		CO2 [kton]
Scenario 3	Conventional	Low Carbon	Total
Total shippers	9.6	$0.4 (T^L)$	193

, in which the purple cell denotes the outcome of the mass-balance formula. Note that the total CO₂-emissions are the same on both sides of the mass balance (green box).

4.2.3. Scenario 3: Maximum Amount of Net Zero Transport by Using a Green Methanol Vessel as Low Carbon Technology

Scenario 3 is also a supply-driven scenario, which is similar to the Scenario 2, but in Scenario 3, the carrier retrofits one vessel to a bio-methanol vessel. The question to be answered using the mass balance methodology is how much net zero transport activity the carrier can sell to its customers. Table 9 shows the operation side of the mass balance, in which the bio-methanol vessel produces a total transport activity of 0.4 × 10⁹ tnm, representing 4% of the total TOC transport activity.

Similar to the Scenario 2 elaboration, an application of the mass-balancing formulation of inequality (11) on the carbon intensity of the low-carbon technology bio-methanol (1.5 gCO₂/tnm see Table 4) yields the following maximum amount of net zero transport activity that can be sold to the shippers:

$$T^L\ge T^Z\frac{I^C}{I^C-I^L}=0.06\times \frac{20}{20-16.8}\cong 0.38$$

(15)

In this scenario, the maximum amount of net zero transport activity that can be sold is 0.37 × 10⁹ tnm with an amount of 0.4 × 10⁹ tnm of low-carbon (green methanol) transport activity in the operation. In this scenario, there is enough conventional transport volumes to be shifted to low-carbon operations. This results in the mass balance as presented in

Table 10. The operation and the administration side of the mass balance in Scenario 2.

	Operation			Administration
	Transport Activity [109 tnm]		CO2 [kton]	CO2 [kton]	Transport Activity [109 tnm]
Scenario 2	Conventional	Low Carbon	Total	Total	Conventional	Net Zero
Total shippers	9.6	$0.4 (T^L)$	193	193	9.63	$0.37 (T^Z)$

, in which the purple cell denotes the outcome of the mass balance formula. Note that the total CO₂-emissions are the same on both sides of the mass balance (green box).

4.3. Practical Notes on Implementation of the Methodology in the Maritime Sector

For implementation of this mass balance methodology, carriers need to have access to data on the emissions of their fleet and data on the amount of transport activity carried out in the network on both the individual shipper level and the fleet level. In maritime shipping, owners and operators of ships greater than 5000 gt making commercial voyages into, out of, or between EU ports are required to report data on their carbon emissions under the Monitoring, Reporting and Verification Regulation (Regulation (EU) 2015/757) [52]. This regulation requires them to share data on the total distance sailed for voyages into, out of, or between EU ports, the associated fuel usage, and the shipped cargo (ton freight or passengers). Reports need to be delivered on an annual basis, and aggregated data is published on a ship level in an EU-wide database.

The data that is gathered by the owners and operators is very suitable and, as shown in this chapter, sufficient for the CO₂ mass balance calculations. For the calculations on the performance on a fleet level, no additional input is required. In order to allocate the CO_2eq emissions to individual shippers, additional input is needed to calculate the share in transport activity (in tonne-nm) of the particular shipper. This requires data on the cargo sailed and the distance sailed (distance between origin and destination ports). This data often is available in the systems of the carriers but are sometimes difficult to combine in one overview. The existing methodologies, such as EN 16258, Lean and Green/BigMile, the GLEC Framework and under the development ISO 14083 standard, provide methods for emission allocation to the individual shipments and carriers. To be trusted, especially in the context of interorganizational relations, computations of carbon footprint and mass-balance method applications may require third party audit.

5. Discussion

The mass balance solution allows product segmentation by the carriers to satisfy demand for net zero emission transport on the part of transport users, or to sell net zero transport volumes as a result of technological shift to low-carbon solutions in practice. The mass balance formulation is sensitive to the carbon intensity of low-carbon solutions that replace conventional ones. This sensitivity is visualized in the mass balance curve (see Figure 6), which shows the amount of low-carbon volumes necessary to provide net zero emission transport depending on the carbon intensity ratio of low-carbon transport to conventional one. Figure 6 also depicts the place of the two low-carbon technologies that were applied in the application case. A low-carbon technology with relatively low CO₂-reduction potential (e.g., 30% bio-blend) requires a relatively high factor of transport activity that needs to be shifted from conventional to this technology to provide net zero transport. In the case of a 30% bio-blend this mass balance factor is 6.3, while this factor is only around 1.1 in case of green methanol. The description of the mass balance factor can be found in Equation (12) in Section 3.

The mass balance curve determines the trade-off between different low-carbon technologies that a carrier can apply in its operations. It also shows the limitation of technologies that only provide a small CO₂-reduction, and hence limited volumes of net zero transport activity that can be sold. There can possibly be a practical discussion on (estimation of) emission intensity of different fuels and technological solutions, but this paper leaves that discussion out of the scope by accepting the emission intensity factors of fuels as a given.

In addition to the sensitivity of the mass balance method to the carbon intensity of the low-carbon solutions, provision of net zero transport services based by low-carbon transport relies on the existence of conventional services in the system. Inequalities (10 and 11) specify the necessary low-carbon volumes that imply that there must be enough conventional transport in the system that can be replaced by low-carbon solutions. Paradoxically, when all conventional transport volumes are replaced by the low-carbon transport, a firm would not be able to offer new zero emission transport products. Nonetheless, this problem is a desired outcome of decarbonization efforts. One of the possible next steps when the state of exhausted conventional volumes is reached is to consider the current low-carbon transport as the conventional and introduce one new low-carbon transport solution with a smaller carbon intensity factor, for example shifting from a HVO mix (Technology 1 in Section 4) to methanol propulsion (Technology 2 in Section 4). Nonetheless, the carriers who already substantially reduced their GHG emissions benefit from this fact too, as the scope 3 emissions [53] of the shippers are also lower in the baseline.

It should be further noted that the carbon intensity of transport solutions is not known ex-ante. Carbon footprinting works with the ex-post data: the carbon intensities of conventional transport I^C and of low-carbon transport I^L depend on many factors, such as utilization rate of vehicles, spatial development of goods flows, economic development, weather, and others. For stable operations, the values of previous periods may provide sufficiently good estimations, but they would still remain unprecise with a certain level of uncertainty. Moreover, when a carrier provides the market with net zero emission products, the volumes are sold before the operations are carried out in the future. The uncertainty in intensity parameters manifests in uncertain estimation of the needed low-carbon transport volumes.

This can be overcome by analyzing the development of carbon intensity values for a number of previous periods. To be on a safe side, the carrier will need to make sure that there is more low-carbon transport in the system than inequalities 10 and 11 strictly specify. Therefore, the uncertainty in intensity parameter further encourages decarbonization efforts. Failure to deliver on the promised net zero emission transport volumes would constitute a breach of the contract and will be made clear by a third party auditor.

Furthermore, the mass balance factor favors shift to low-carbon transport in those networks, where conventional transport emission intensity is high: less low-carbon transport is needed to satisfy specific net zero emission transport demand. This may incentivize the carriers to overestimate carbon intensity of the conventional transport. To ensure that it does not happen in practice, a standardized carbon footprinting method has to be used for determining emission intensity factors. The currently under-development ISO 14083 standard can be considered as such standardized and universally accepted methodology. There is a clear role for the auditors to check that computations are done conform the standard.

6. Conclusions and Recommendations

Freight transport and logistics is one of the important economic sectors contributing to greenhouse gases emissions. This sector is also one of the most difficult to decarbonize in practice. There exist different technologies that allow reducing emissions from transport. These technologies are mostly related to electrification and use of greener fuels. The use of these low-carbon technologies still results in GHG emissions, but in a lesser emission volume than in case of conventional ones. The low-carbon technologies are generally more expensive than conventional technologies, so their use needs to overcome a certain amount of financial resistance.

Fortunately, there is substantial demand for decarbonization in transport and logistics. This demand comes mostly from the users of transport (i.e., shippers), who make decisions on how their goods are shipped. Larger shippers, especially those with access to the public debt and equity financing, may find decarbonization to be financially attractive, as the extra costs of decarbonization may be offset by the lower costs of capital. Therefore, part of the demand for transport services is willingness to pay a premium for low-carbon or zero-emission transport services. It should also be underscored that a substantial part of transport demand is still not interested in decarbonization if it entails extra costs.

The research presented in the paper proposes a mass-balancing method based on carbon footprinting procedures in compliance with the future ISO 14083 standard on quantification of GHG emissions in transport and logistics. The mass-balancing method allows carriers to cater to demand for zero emission transport services, without the need to create dedicated subsystems to satisfy this green transport demand and thus without physical segmentation that may reduce the overall efficiency of the transport solutions. Using the presented mass-balance method, a carrier ensures that the volumes sold as ‘zero emission’ do not contribute to real world emissions, while these transport volumes may be physically carried out by the conventional transport means. The proposed method allows provision of net zero transport services using low-carbon technologies by requiring additional volumes of low-carbon transport to compensate for the non-zero emission nature of low-carbon transport solutions. The method provides for quantification of the needed volume of low-carbon transport to satisfy certain demand for zero emission transport (demand side), and for quantification of zero emission transport volumes given the known quantity of low-carbon transport (supply side).

The developed method has been applied on real world data of a deep-sea carrier. The application case has shown that data requirements for implementation of the method are not heavy for a carrier. The data required is the same as for carbon footprinting (i.e., TOC-level transport activity and emissions) and should be collectable within reasonable effort at any carrier. Moreover, due to a European MRV regulation, the data should already be available at any deep-sea carrier serving European ports with the vessels larger than 5000 gt. The practical case scenarios looked at what volume of low-carbon emission transport are needed to satisfy certain zero emission transport demand and what volumes of zero emission transport can be provided given technology shift on the carrier’s side. The application case shows how the method can be made understandable for the auditors by providing conceptual separation of “operations” and “accountancy”.

The authors recommend to conduct further research along the following two broad research opportunities. The first one is related to the costs of decarbonization. At this moment, low-carbon solutions for transport and logistics are generally more expensive than the conventional ones, but a good overview of the costs related to decarbonization is missing. For instance, information on CO₂ abatement cost per tonne of CO₂ saved, and abatement costs per tonne-kilometre shipped, would help prioritize decarbonization measures, such that public and private spending on decarbonization is prioritized into those areas where the limited resources can achieve the maximum effect. The second research opportunity relates to further development of carbon footprinting methods and related data exchange mechanisms between participants in transport and supply chains. A possible European legislation on collection and sharing of emission data along transport chains can provide an impetus for the research and development in this area.