The International Maritime Organization (IMO) has adopted a strategy to reduce emissions from international shipping that sets very ambitious targets. The first set of actions, so-called short-term measures, are expected to be implemented by 2023 and result in a reduction of emission intensity by at least 40% by 2030 compared with 2008 levels. Compliance may be achieved through a reduction in sailing speeds, but certain countries have raised concerns on the ramifications of longer transit times on their exports, particularly for perishable products. In this paper, we present a methodology to assess the impacts of various short-term measures on perishable products. We use an extension of a nested modal split model to examine shifts towards other modes of transport. We demonstrate our methodology with a transpacific case study carrying perishable products from South America to China. We compare the short-term measures currently under discussion, in one of the first academic studies to explore these issues. These include a speed limit approach, a power limit, and a goal-based measure. Our results show that a power limit or a goal-based measure would offer some advantages to liner shipping operators using more efficient vessels, unlike a speed limit. Using 2008 as the benchmark year has resulted in small speed reductions required by the liner shipping sector to reach its targets. For perishable cargoes, small speed reductions can be tolerated by the shippers without significant modal shift. Choosing the right short-term strategy is of utmost importance to promote clean shipping practices in the following years.
To achieve IMO’s goal of a 50% reduction of GHG emission by 2050 (compared to the 2008 levels), shipping must not only work towards an optimization of each ship and its components but aim for an optimization of the complete marine transport system, including fleet planning, harbour logistics, route planning, speed profiles, weather routing and ship design. ShipCLEAN, a newly developed model, introduces a coupling of a marine transport economics model to a sophisticated ship energy systems model – it provides a leap towards a holistic optimization of marine transport systems. This paper presents how the model is applied to propose a reduction in fuel consumption and environmental impact by speed reduction of a container ship on a Pacific Ocean trade and the implementation of wind assisted propulsion on a MR Tanker on a North Atlantic trade. The main conclusions show that an increase of the fuel price, for example by applying a bunker levy, will lead to considerable, economically motivated speed reductions in liner traffic. The case study sowed possible yearly fuel savings of almost 21 300 t if the fuel price would be increased from 300 to 1000 USD/t. Accordingly, higher fuel prices can motivate the installation of wind assisted propulsion, which potentially saves up to 500 t of fuel per year for the investigated MR Tanker on a transatlantic route.
Discusses the challenges of raising finance to build and convert low- and zero-emission ships as required by international law and policy to mitigate climate change.
The purpose of this paper is to investigate a multiple ship routing and speed optimization problem under time, cost and environmental objectives. A branch and price algorithm as well as a constraint programming model are developed that consider (a) fuel consumption as a function of payload, (b) fuel price as an explicit input, (c) freight rate as an input, and (d) in-transit cargo inventory costs. The alternative objective functions are minimum total trip duration, minimum total cost and minimum emissions. Computational experience with the algorithm is reported on a variety of scenarios.
This study concerns nitrogen based emissions from a hydrogen enriched ammonia fueled SI engine. These emissions deserve special attention as their formation may differ from conventional HC combustion due to the nitrogen content in the fuel. A range of experiments are conducted with a single cylinder 0.612 l CFR engine with a compression ratio varying from 7 to 15 using a fuel composition of 80 vol% NH3 and 20 vol% H2. Wet exhaust samples are analysed with an FT-IR. Emission measurements reveal that nitric oxide stem from other reaction paths than the dissociation of molecular nitrogen. This causes the NO emissions to peak around 35% rather than 10% excess air, as is typical in HC fueled SI-engines. However the magnitude of NO emissions are comparable to that of measurements conducted with gasoline due to lower flame temperatures. Nitrogen dioxide levels are higher when comparing with gasoline, but has a relatively low share of the total NOx emissions (3–4%). Nitrous oxide is a product of NH2 reacting with NO2 and NH reacting with NO. The magnitude is largely affected by ignition timing due to the temperature development during expansion and the amount of excess air, as increased oxygen availability stimulates the formation of the NH2 radical and the levels of NO2 are higher. Under ideal operating conditions (MBT ignition timing) N2O levels are very low. The dominating contributors to unburned ammonia are chamber crevices as the magnitude of these emissions is greatly affected by the compression ratio. However, levels are lower than required in order to eliminate all NOx emissions with a SCR catalyst.
This paper presents a detailed BC, NOx and SO2 emission inventory for ships in the Arctic in 2012 based on satellite AIS data, ship engine power functions and technology stratified emission factors. Emission projections are presented for the years 2020, 2030 and 2050. Furthermore, the BC, SO2 and O3 concentrations and the deposition of BC are calculated for 2012 and for two arctic shipping scenarios – with or without arctic diversion routes due to a possible polar sea ice extent in the future.
In 2012, the largest shares of Arctic ships emissions are calculated for fishing ships (45% for BC, 38% for NOx, 23% for SO2) followed by passenger ships (20%, 17%, 25%), tankers (9%, 13%, 15%), general cargo (8%, 11%, 12%) and container ships (5%, 7%, 8%). In 2050, without arctic diversion routes, the total emissions of BC, NOx and SO2 are expected to change by +16%, −32% and −63%, respectively, compared to 2012. The results for fishing ships are the least certain, caused by a less precise engine power – sailing speed relation.
The calculated BC, SO2, and O3 surface concentrations and BC deposition contributions from ships are low as a mean for the whole Arctic in 2012, but locally BC additional contributions reach up to 20% around Iceland, and high additional contributions (100–300%) are calculated in some sea areas for SO2. In 2050, the arctic diversion routes highly influence the calculated surface concentrations and the deposition of BC in the Arctic. During summertime navigation contributions become very visible for BC (>80%) and SO2 (>1000%) along the arctic diversion routes, while the O3 (>10%) and BC deposition (>5%) additional contributions, respectively, get highest over the ocean east of Greenland and in the High Arctic.
The geospatial ship type specific emission results presented in this paper have increased the accuracy of the emission inventories for ships in the Arctic. The methodology can be used to estimate shipping emissions in other regions of the world, and hence may serve as an input for other researchers and policy makers working in this field.
Enhancing environmental sustainability in maritime shipping has emerged as an important topic for both firms in shipping-related industries and policy makers. Speed optimization has been proven to be one of the most effective operational measures to achieve this goal, as fuel consumption and greenhouse gas (GHG) emissions of a ship are very sensitive to its sailing speed. Existing research on ship speed optimization does not differentiate speed through water (STW) from speed over ground (SOG) when formulating the fuel consumption function and the sailing time function. Aiming to fill this research gap, we propose a speed optimization model for a fixed ship route to minimize the total fuel consumption over the whole voyage, in which the influence of ocean currents is taken into account. As the difference between STW and SOG is mainly due to ocean currents, the proposed model is capable of distinguishing STW from SOG. Thus, in the proposed model, the ship’s fuel consumption and sailing time can be determined with the correct speed. A case study on a real voyage for an oil products tanker shows that: (a) the average relative error between the estimated SOG and the measured SOG can be reduced from 4.75% to 1.36% across sailing segments, if the influence of ocean currents is taken into account, and (b) the proposed model can enable the selected oil products tanker to save 2.20% of bunker fuel and reduce 26.12 MT of CO2 emissions for a 280-h voyage. The proposed model can be used as a practical and robust decision support tool for voyage planners/managers to reduce the fuel consumption and GHG emissions of a ship
Havebrugsindustrien i nordiske lande er meget afhængig af drivhussystemer på grund af begrænsningen af det naturlige miljø og de strenge plantekrav for bestemte plantetyper. Kommercielle avlere i disse regioner støder på betydelige udfordringer med at garantere kvaliteten af planterne, mens de minimerer produktionsomkostningerne. På den ene side skal et drivhussystem forbruge en stor mængde energi for at give et tilfredsstillende klima for plantevækst. På den anden side, i de senere år, har energiprisen stigende i Europa ført til en stigning i produktionsomkostningerne for drivhuse, hvilket gør energibesparelse og optimering imperativ. Det er dog udfordrende for avlere at håndtere dette dilemma, fordi drivhusklimakontrol er et meget dynamisk og meget koblet komplekst system. Ved at analysere funktionerne i ikke-linearitet og dynamik i drivhusklimaet kan de eksisterende løsninger ikke korrekt opfylde de praktiske krav i gartneriindustrien.
For at tackle disse problemer foreslås en digital tvilling af drivhusklimakontrol (DT-GCC) rammer i denne forskning for at optimere aktuatorens driftsplan til minimering af energiforbrug og produktionsomkostninger uden at gå på kompromis med produktionskvaliteten. Arkitekturen i DT-GCC-rammen og de anvendte metoder er uddybet modulært, herunder fysisk tvilling af drivhusklimakontrol (PT-GCC) systemforståelse, design af DT-GCC-system, sammenkobling af DTGCC og PT-GCC og integration med andre digitale tvillinger (DTS).
DT-GCC omfatter en virtuel drivhus (VGH) og en multi-objektiv optimeringsbaseret klimakontrol (MOOCC) platform. VGH er den digitale repræsentation af det fysiske drivhus gennem modellering af de faktorer, der kan påvirke drivhusklimaet markant og aktuatorens driftsstrategier. MOOCC er ansvarlig for at definere drivhusklimakontrol som et multi-objektivt optimeringsproblem (MOO) og optimere driftsplanen for kunstigt lys (lysplan) og varmesystem (varmeplan). Desuden er en hierarkisk struktur af DT-GCC designet i henhold til funktionerne og ansvaret for individuelle lag, der gavner den praktiske realisering af DT-GCC med en organiseret arkitektur af design og styring.
Funktionaliteterne i DT-GCC er udviklet i en drivhusklimakontrolplatform, der er navngivet af Dynalight, som er kombineret med en genetisk algoritme (GA) ramme kaldet Controleum. Dynalight definerer et MOO -problem til at abstrahere drivhusklimakontrolsystemet med flere objektive funktioner, og omkostningerne beregnes baseret på modelleringsresultaterne fra VGH. Controleum er ansvarlig for implementeringen af GA for at generere en Pareto Frontier (PF) og endelig løsning af løsning til let plan og varmeplan.
Forskellige scenarier og tilsvarende eksperimenter er designet til at evaluere ydelsen af DT-GCC fra individuelle perspektiver, herunder VGH, MOOCC og DT-integration. Eksperimenterne på VGH verificerer forudsigelsesydelsen for kunstigt neuralt netværk (ANN) metoder på indendørs temperatur, opvarmning af forbrug og netto fotosyntese (PN). Hvad angår de to standaloneeksperimenter, garanterer resultaterne DT-GCCs evne til at kortlægge avlernes beslutningstagning om let plan og varmeplan og verificere MOOCC-ydelsen for at opfylde voksende krav og samtidig reducere energiforbruget og omkostningerne. Endelig, i DT-integrationseksperimenterne med Digital Twin of Production Twin (DT-PF) og Digital Twin of Energy System (DT-ES), afslutter DT-GCC det tilsvarende svar på forudsigelser og optimeringsanmodninger.
The Belt and Road Initiative (BRI) entails investments to improve overland (rail) transport between Europe and China. This paper introduces a microscopic Multi-Commodity Flow Service Selection Problem for freight transport under the BRI and provides a decision tool for shippers to make door-to-door service plans. The minimizing objective function considers transportation costs, in-transit inventory costs, and carbon emissions. A series of sampled data of each provincial region of China are collected from Chinese multimodal transport operators. Results show that inland regions are strongly attracted to the rail mode for shipments to Europe. However, the “last mile” (including “first mile”) transport from the shipper to the long-haul transport terminal strongly influences this choice, and carbon emissions are strongly influenced by the available last mile transport links. Under the dual impact of in-transit inventory and carbon emission costs, regions that prefer rail to maritime are much further east than suggested by previous literature.
Hydrogen energy is a promising solution for prompting low-carbon port development. This study introduces two hydrogen utilization strategies: hydrogen consumption-driven strategy (HCDS) and hydrogen storage-driven strategy (HSDS). Using data from a real port and a life-cycle assessment approach, a case study is conducted to compare their economic and ecological performances. The results show that HCDS enhances economic benefits, with an annualized cost of 66.1 million CNY, which is 11% lower than HSDS. Additionally, HCDS is sensitive to electricity prices and grid carbon emission factor. In contrast, HSDS offers superior ecological benefits, with an annualized carbon footprint of 31,300 tons of CO₂, which is 12% lower than HCDS, and is mainly sensitive to purchase prices and emission factors of electricity and hydrogen. This study provides critical insights into the trade-offs between economic and ecological performance under different hydrogen utilization strategies, offering practical guidance for implementing hydrogen energy system applications in ports.