Search Results (52)

The maritime sector is undergoing rapid transformation, driven by increasingly stringent international regulations targeting air pollution. While newly built vessels integrate advanced technologies for compliance, the global fleet averages 21.8 years of age and must meet emission requirements through retrofitting or operational changes. This study evaluates, at environmental and economic levels, two key sulphur abatement strategies for a 1998-built cruise vessel nearing the end of its service life: (i) the installation of open-loop scrubbers with fuel enhancement devices, and (ii) a switch to marine diesel oil as main fuel. The analysis was based on real operational data from a cruise vessel. For the environmental assessment, a Tier III hybrid emissions model was used. The results show that scrubbers reduce SO_x emissions by approximately 97% but increase fuel consumption by 3.6%, raising both CO₂ and NO_x emissions, while particulate matter decreases by only 6.7%. In contrast, switching to MDO achieves over 99% SO_x reduction, an 89% drop in particulate matter, and a nearly 5% reduction in CO₂ emissions. At an economic level, it was found that, despite a CAPEX of nearly USD 1.9 million, scrubber installation provides an average annual net saving exceeding USD 8.2 million. From the deterministic and probabilistic analyses performed, including Monte Carlo simulations under various fuel price correlation scenarios, scrubber installation consistently shows high profitability, with NPVs surpassing USD 70 million and payback periods under four months. Full article

Investigating biodiversity in remote and harsh environments, particularly in the Southern Ocean, remains costly and challenging through traditional sampling methods such as trawling. Environmental DNA (eDNA) sampling, which refers to sampling genetic material shed by organisms from environmental samples (e.g., water), provides a more cost-effective and sustainable alternative to traditional sampling approaches. To study the biogeographic patterns of two typical mesopelagic fishes, Antarctic lanternfish (Electrona antarctica) and Antarctic deep-sea smelt (Bathylagus antarcticus), in the Cosmonaut Sea in the Indian Ocean sector of the Southern Ocean, we conducted both eDNA and trawling sampling at a total of 86 stations in the Cosmonaut Sea during two cruises in 2021–2022. Two sets of species-specific primers and probes were developed for a quantitative eDNA analysis of two fish species. Both the eDNA and trawl results indicated that the two fish species are widely distributed in the Cosmonaut Sea, with no significant difference in eDNA concentration, biomass, or abundance between stations. Spatially, E. antarctica tended to be distributed in shallow waters, while B. antarcticus tended to be distributed in deep waters. Vertically, E. antarctica was more abundant above 500 m, while B. antarcticus had a wider range of habitat depths. The distribution patterns of both species were affected by nutrients, with E. antarctica additionally affected by chlorophyll, indicating that their distribution is primarily influenced by food resources. Our study provides broader insight into the biogeographic patterns of the two mesopelagic fishes in the remote Cosmonaut Sea, demonstrates the potential of combining eDNA with traditional methods to study biodiversity and ecosystem dynamics in the Southern Ocean and even at high latitudes, and contributes to future ecosystem research and biodiversity conservation in the region. Full article

Recently, as carbon emission regulations enforced by the International Maritime Organization (IMO) have become stricter and pressure from the World Trade Organization (WTO) to abolish tax-free fuel subsidies has increased, the demand for electric propulsion systems in the marine sector has grown. Most small domestic fishing vessels rely on tax-free fuel and have limited cruising ranges and constant-speed operation, which makes them well-suited for electric propulsion. This paper proposes replacing the internal combustion engine system of such vessels with an electric propulsion system. Based on real operating conditions, an Interior Permanent Magnet Synchronous Motor (IPMSM) was designed and optimized. The Savitsky method was used to calculate total resistance at a typical cruising speed, from which the required torque and output were determined. To reduce torque ripple, an asymmetric dummy slot structure was proposed, with two dummy slots of different widths and depths placed in each stator slot. These dimensions, along with the magnet angle, were set as optimization parameters, and a metamodel-based optimal design was carried out. As a result, while meeting the design constraints, torque ripple decreased by 2.91% and the total harmonic distortion (THD) of the back-EMF was lowered by 1.32%. Full article

The hospitality and tourism (H&T) sector, marked by intense employee–customer interactions, dynamic labor shifts, and high physical and emotional labor demands, faces chronic talent acquisition and retention. Therefore, tailored employer branding (EB) strategies that address the unique characteristics of the H&T sector are essential for improving the current situation. Despite the critical need for tailored solutions, a clear and unified approach for H&T companies to effectively manage their EB strategies, including the development of a compelling employee value proposition (EVP) that resonates with targeted professionals, has yet to be established. Following the PRISMA reporting guidelines, a systematic literature review of 30 peer-reviewed articles from the Scopus and Web of Science databases was conducted to synthesize existing research on EB practices in the H&T sector. The results reveal a fragmented literature that lacks a cohesive framework for categorizing and measuring EVP. The use of varied and inconsistent EVP models and scales across studies hampers comparative analysis and limits the development of generalizable insights. Furthermore, the review highlights a concentration of research within the hotel industry, leaving other important H&T industries, such as the restaurant and cruise industries, underexplored. This SLR emphasizes the urgent need for a unified approach to EB in H&T. Based on these results, promising research avenues are suggested to further advance EB research in H&T, along with managerial implications for enhancing talent attraction and retention in the sector. Full article

Comprehending the dynamics of risk spillover across the value chain is indispensable for effective risk management, especially amid increasing economic and geopolitical uncertainty. This study investigates the mechanics of risk transmission within the value chain of the Chinese hospitality industry by employing a Time-Varying Parameter Vector Autoregression (TVP-VAR) model using daily data from January 2015 to December 2023. Our research identifies key sub-sectors, such as hotel resort and luxury cruises, film and entertainment, malls and supermarkets, environmental and facilities services, air freight and logistics, and road transportation, as significant risk transmitters that affect the overall stability of the industry. Conversely, sectors such as restaurants, liquor and wine services, leisure services, and railway transport are designated as risk receivers. These results offer critical insights for stakeholders, emphasizing the necessity of comprehensive risk management strategies to reduce negative spillover effects, particularly in the context of economic shocks like the COVID-19 pandemic and geopolitical events like the Russia–Ukraine conflict. Full article

Aviation’s non-CO₂ effects account for approximately 66% of the sector’s Effective Radiative Forcing (ERF). However, non-CO₂ emissions and their climate effects are particularly challenging to assess due to the number of variables involved. This research provides a framework for characterizing the full climate impact of individual real-world flights in terms of global surface temperature change (ΔT) with the aid of a validated CFM56-7B26/3 engine model and spatially and temporally resolved meteorological data. Different modelling methods were used to evaluate NO_x and soot emissions and the relative differences between them were quantified, while a contrail formation model was implemented to quantify the distances travelled where persistent contrails were formed. The ΔT was evaluated over 77 years using a Linear Temperature Response Model (LTR). The results show that NO_x-induced effects such as the increase in short-term ozone had the highest impact on ΔT in the first year of emissions, while CO₂ was more detrimental to ΔT in the long term. Unlike the mid and long-range flights examined, the climb segment of the short-range flight had a more significant impact on ΔT than the cruise segment. ΔT sensitivity studies for different emission modelling methods showed differences up to 13% for NO_x and 14% for soot. Full article

Shipping activities continue to experience growth across a multitude of industrial sectors within the Arctic, hence there are risks in terms of severity and likelihood of accidents. The Arctic region is inherently dangerous to transportation and human existence due to its extreme climate and environmental conditions, and hence the complexities associated with emergency situations within the maritime domain are amplified when operating within the Arctic and North-Atlantic (ANA). The definition and characterisation of potential seaborne disasters and catastrophic incidents in the ANA region are significant enablers in providing a set of critical and sustainable tools for Search and Rescue (SAR), Oil Spill Response (OSR), and emergency management practitioners. Therefore, in this paper we aim to identify and characterise high-priority potential seaborne disasters and catastrophic incidents in the ANA region such as cruise ship accidents, oil leaks, radiological leaks, and fishing boat groundings. These were compiled as an outcome of a set of workshops carried out as part of the ARCSAR, EU Horizon 2020 funded project, and from analysis of the literature. We also provide root cause analysis techniques, tools for strategic decision-making, and means of mitigation. We demonstrate how such tools can be used by applying some of them to a selective case study and drawing lessons learned from the application of root cause analysis, which can help emergency response organisations with preparedness work and hence more efficient response. In doing so, we provide a set of tools that can be used for strategic and operational learning. Such approaches can help standardise the definition and characterisation of potential seaborne disasters and catastrophic incidents in the ANA region in both prospective and retrospective analysis. Full article

The shipping industry plays a crucial role in global trade, but it also contributes significantly to environmental pollution, particularly in regard to carbon emissions. The Carbon Intensity Indicator (CII) was introduced with the objective of reducing emissions in the shipping sector. The lack of familiarity with the carbon performance is a common issue among vessel operator. To address this aspect, the development of methods that can accurately predict the CII for ships is of paramount importance. This paper presents a novel and simplified approach to predicting the CII for ships, which makes use of data-driven modelling techniques. The proposed method considers a restricted set of parameters, including operational data (draft and speed) and environmental conditions, such as wind speed and direction, to provide an accurate prediction of the CII factor. This approach extends the state of research by applying Deep Neural Networks (DNNs) to provide an accurate CII prediction with a deviation of less than 6% over a considered time frame consisting of different operating states (cruising and maneuvering mode). The result is achieved by using a limited amount of training data, which enables ship owners to obtain a rapid estimation of their yearly rating prior to receiving the annual CII evaluation. Full article

In order to ensure that aircraft have medium and long-range flights, enhanced aerodynamic performance, and reduced fuel consumption, this paper presents an original Distributed Hybrid Electric Propulsion Aircraft (DHEPA) design scheme and proposes a novel power allocation management method based on convex optimization. Firstly, by taking the Tecnam P2006T general-purpose aircraft as a reference, key components of DHEPA are selected and modeled. Then, a power allocation management method for DHEPA is proposed on the basis of convex optimization, which takes the minimum fuel consumption as the performance index to realize the reasonable power allocation of the battery and engine, while avoiding sliding into the local optimum of allocation. Finally, momentum theory and numerical simulation methods are used to analyze the aerodynamic enhancement effect of the propeller on the wing in the DHEPA, and a dynamics method is utilized to calculate the dynamics performance of the aircraft at several important stages. The results show that, compared with the reference aircraft, the lift of the DHEPA is increased by 46%. Under typical sectors, the DHEPA has a higher rate of climb and maximum leveling off speed at cruise, and a significantly lower fuel consumption. Full article

The rapid growth of urbanization in China has led to a substantial escalation in the demand for civil aviation services, consequently propelling China to the third-largest contributor of carbon emissions within the aviation sector. Using the 2012–2021 data on takeoffs and landings of civil aviation aircraft in China, the aircraft engine emission factor database of the Base of Aircraft Data (BADA) from EUROCONTROL, this paper investigates the spatial-temporal distribution characteristics of atmospheric pollutants, primarily carbon emissions from Chinese civil aviation aircraft in 19 megacities. The results indicate that (1) China’s aviation CO₂ emissions equivalent between 2012 and 2022 has been on an upward trajectory, peaking at 186.53 MT in 2019 with an average annual growth of 12.52%. The trend, albeit momentarily interrupted by the COVID-19 pandemic, appears to persist. (2) CO₂ constitutes the highest proportion of aircraft emissions at 83.87%, with Cruise Climb Descent (CCD) cycle emissions accounting for 96.24%. CO₂ and NO_X, with the highest increase rates in the CCD and Landing and Takeoff (LTO) phases, respectively, are identified as the chief culprits in aviation-related greenhouse effects. (3) There is a marked spatial imbalance, with 19 megacities contributing 62.08% of total CO₂ emissions, compared to the 207 least-emitting cities contributing just 9.29%. (4) The pattern of city carbon emissions is changing, with rapid growth rates in the western cities of Xinjiang, Tibet, Shaanxi, and Guizhou, and varied growth rates among megacities. The implications of this study emphasize the urgency for advancements in aviation fuel technology, rigorous management of CCD phase pollutants, strategic carbon emission controls in populous cities, fostering green aviation initiatives in western regions, diverse carbon mitigation tactics, and strengthening the precision and surveillance of aviation carbon accounting systems. Collectively, this study paints a grand picture of the complexities and challenges associated with China’s urban sprawl and aviation carbon emissions. Full article

Cities attract a large number of inhabitants due to their more advanced industrial and commercial sectors and more abundant and convenient living conditions. According to statistics, more than half of the world’s population resides in urban areas, contributing to the prosperity of cities. However, it also brings more crime risks to the city. Crime prediction based on spatiotemporal data, along with the implementation of multiple unmanned drone patrols and responses, can effectively reduce a city’s crime rate. This paper utilizes machine learning and data mining techniques, predicts crime incidents in small geographic areas with short timeframes, and proposes a random forest algorithm based on oversampling, which outperforms other prediction algorithms in terms of performance. The research results indicate that the random forest algorithm based on oversampling can effectively predict crimes with an accuracy rate of up to 95%, and an AUC value close to 0.99. Based on the crime prediction results, this paper proposes a multi-drone patrol response strategy to patrol and respond to predicted high-crime areas, which is based on target clustering and combined genetic algorithms. This strategy may help with the pre-warning patrol planning within an hourly range. This paper aims to combine crime event predictions with crowd-sourced cruise responses to proactively identify potential crimes, providing an effective solution to reduce urban crime rates. Full article

Over the years, attention to climate change has meant that international agreements have been drawn up and increasingly stringent regulations aimed at reducing the environmental impact of the marine sector have been issued. A possible alternative technology to the conventional and polluting diesel internal combustion engines is represented by the Fuel Cells. In the present article, the preliminary design of two energy systems based on Solid Oxide Fuel Cells (SOFCs) fed by bio-methane was carried out for a particular cruise ship. The SOFC systems were sized to separately supply the electric energies required for the ship propulsion and to power the other ship electrical utilities. The SOFC systems operate in nominal conditions at constant load and other electrical storage systems (batteries) cover the fluctuations in the electrical energy demand. Furthermore, the heat produced by the SOFCs is exploited for co-/tri-generation purposes, to satisfy the ship thermal energy needs. The preliminary design of the new energy systems was made using electronic spreadsheets. The new energy system has obtained the primary energy consumption and CO₂ emissions reductions of 12.74% and 40.23% compared to the conventional energy system. Furthermore, if bio-methane is used, a reduction of 95.50% could be obtained in net CO₂ emissions. Full article

In our increasingly interconnected world, the idea of global citizenship has taken center stage, especially in alignment with the UN’s Sustainable Development Goals. At the same time, the cruise sector, in its resurgence after the COVID-19 setback, is facing workforce equilibrium issues. This study delves into career guidance, specifically concerning cruise staff roles. The focus is on how global citizenship perceptions, work-related values, service-oriented attitudes, competencies, and career self-concepts interplay among emerging service professionals. Initially, the global perspective of these professionals considerably boosts their work values, attitudes, and competencies related to cruise ship roles. Furthermore, a positive service attitude enhances work values and competencies. Also, work values appear to augment both skill sets and career self-awareness among cruise staff. The skills of cruise staff significantly amplify their career self-concept. Moreover, both the service mindset and skill set of cruise staff serve as intermediaries in the nexus between global citizenship, work values, and career identity. Lastly, the service perspective, abilities of cruise staff, and job values are pivotal links between global citizenship views, occupational values, and career recognition. The findings underline the significance of fostering a global outlook, emphasize the alignment of job selections with work values, and accentuate the importance of building service mindsets and capabilities for robust career self-awareness. A dual approach, incorporating global citizenship teachings and skill-building for cruise roles, can help bridge the workforce gap in the cruise sector. In essence, these findings can enlighten cruise companies as they evaluate the community involvement facet of their ESG directives. Full article

Passenger cars account for the largest share of GHG emissions in the road sector. However, given that the number of heavy-duty vehicles registered is lower but accounts for about a quarter of GHG emissions in the road sector, it is necessary to reduce carbon dioxide (CO₂) emissions by improving the fuel efficiency of heavy-duty vehicles. However, experiments using dynamometers during the vehicle development process consume a lot of time and cost. Conversely, simulations can quantitatively analyze the sensitivity of parameters and accelerate optimization. Therefore, in this study, we modeled a heavy-duty vehicle using an AVL Cruise simulation and analyzed the effects of payload, air drag coefficient, and rolling resistance on fuel economy, CO₂ emission, and the valid window ratio among the moving average window (MAW) for three driving routes. When the average vehicle speed was higher, the effect of the air drag coefficient on fuel economy was high. Additionally, when the average vehicle speed was lowered, the effect of the reduced rolling resistance on improving fuel efficiency was higher than that of the reducing air drag. Thus, the fuel efficiency improvement rate according to each 10% decrease in rolling resistance was higher by 2.2%, on average, in the low average speed route. Additionally, it was confirmed that the valid window ratio was high when driving in a section with a high vehicle speed first. Thus, the valid window ratio was almost 100% in the test of the route conditions starting from the highway section. Full article

The development of high-tech, dim, small targets, such as drones and cruise missiles, brings great challenges to radar multi-target tracking (MTT), making it necessary to extend the beam dwell time to obtain a high signal-to-noise ratio (SNR). In order to solve the problem of radar sampling time variation exacerbated by extending the beam dwell time when detecting weak targets, a sector-matching (SM) PHD filter is proposed, which combines the actual radar system with a PHD filter and quantifies the relationship between the beam dwell time, the false alarm rate and the detection probability. The proposed filter divides the scanning area into small sectors to obtain actual multi-target measurement times and rederives the prediction and update steps based on the actual sampling time. Furthermore, a state correction step is added before state extraction. Applying the SM structure to the basic Gaussian mixture PHD (GM-PHD) filter and labeled GM-PHD filter, the simulation results demonstrate that the proposed structure can improve the accuracy of multi-weak-target state estimation in the dense clutter and can continuously generate explicit trajectories. The overall real-time performance of the proposed filter is similar to that of the PHD filter. Full article