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Modern ports tend to focus on freight transport and cruise traffic. The fishing sector is often the forgotten sector in terms of sustainability and port planning, despite the fact that fishing is a sector of great importance and interest; though it is currently obsolete in many respects. Literature on sustainability and green ports in the context of fishing ports is practically non-existent; however, it is necessary in order to implement a sustainable fishing infrastructure. For this reason, the aim of this study is, within the green ports framework as outlined by the European Commission and using an innovative end-to-end tool methodology, to determine the reality of the conditions of the port environment in fishing ports. Furthermore, this study establishes a possible green ports scenario for Spanish fishing ports and carries out an analysis of a specific case study within the Spanish port system: the Port of Vigo. It is concluded that the key fishing features of the Port of Vigo should, in order to expand its sustainability strategies, are: growth expectations, closely related to the evolution of the goods unloaded in the Port of Vigo and the possible growth that this may have in the future; legislation and current trends in terms of sustainability; and diversification, the Port of Vigo has realistic options to diversify the business beyond the traditional fishing activities.

Electric vehicles are able to provide immediate power through the vehicle-to-grid function, and they can adjust their charging power level when in the grid-to-vehicle mode. This allows them to provide ancillary services such as frequency control. Their batteries differ from conventional energy storage systems in that the owner’s energy requirement constraint must be met when the vehicles participate in a frequency control system. An optimization problem was defined by considering both the owner satisfaction and frequency control performance. The main contribution of the proposed paper, compared to the literature, are (1) to keep the total available energy stored in the batteries connected to a charging station in an optimal region that favors the frequency regulation capability of the station and the proposed QoS and (2) to consider the optimal region bounded by the efficiency thresholds of the charger to allow for maximum regulation power. The problem is expressed as a multi-criteria optimization problem with time-dependent references. The paper presents an energy management strategy for frequency control, describes a concept of an optimal time-dependent state of charge for electric vehicle charging demands, and considers the power dependence of the electric vehicle charger efficiency. Finally, the simulation results are presented via Matlab/Simulink to prove the effectiveness of the proposed algorithm.

In light of the increasing number of electric vehicles (EV), disorderly charging in mountainous cities has implications for the stability and efficient utilization of the power grid. It is a roadblock to lowering carbon emissions. EV aggregators are a bridge between EV users and the grid, a platform to achieve energy and information interoperability, and a study of the orderly charging of EVs to reach carbon emission targets. As for the objective function, the EV aggregator considers the probability of EV charging access in mountainous cities, the SOC expectation of EV users, the transformer capacity constraint, the charging start time, and other constraints to maximize revenue. Considering the access probability of charging for users in mountainous cities, the optimized Lagrange relaxation method is used to solve the objective function. The disorderly charging, centralized optimized charging, and decentralized optimized charging modes are investigated using simulation calculations. Their load profiles, economic benefits, and computational efficiency are compared in three ways. Decentralized optimal charging using the Lagrange relaxation method is shown to be 50% more effective and to converge 279% faster than centralized optimal charging.

The paper represents the analysis, which has helped to establish the usage of gas hydrate technologies in the methane conversion. This gas could be obtained in different ways. Possibilities and sources for the gas obtaining have been demonstrated. Use of other environmentally friendly sources to support operation in such systems in terms of joint energy complex has been considered. The necessary kinetic connections to provide operational sustainability of all the constituents have been given. The approach helps evaluate quantitatively the priority of its physicochemical transformations to obtain gas hydrates artificially. It is possible to transport methane at considerable distances when it is solidified. Actually, in this case there is no necessity to build costly compressor stations and pipelines for its transportation to consumers. The approach is extremely important for mining regions as it helps prolong the operating period and working out of the abandoned and off-balance coal reserves. In this case, it is proposed to apply special gasification technologies tending to maximum methane recovery. The proposed solutions give the possibility to define the trends of our further research. They will be highlighted in the following authors’ studies.

Uncertainty surrounding the potential environmental impacts of marine energy (ME) has resulted in extensive and expensive environmental monitoring requirements for ME deployments. Recently, there have been more ME deployments and associated environmental data collection efforts, but no standardized methodologies for data collection. This hinders the use of previously collected data to inform new ME project permitting efforts. Triton Field Trials (TFiT), created at the Pacific Northwest National Laboratory by the United States (U.S.) Department of Energy, explores ways to promote more consistent environmental data collection and enable data transferability across ME device types and locations. Documents from 118 previous ME projects or ME-related research studies in the U.S. and internationally were reviewed to identify the highest priority stressor–receptor relationships to be investigated and the technologies and methodologies used to address them. Thirteen potential field sites were assessed to determine suitable locations for testing the performance of relevant monitoring technologies. This introductory paper provides an overview of how priority research areas and associated promising technologies were identified as well as how testing locations were identified for TFiT activities. Through these scoping efforts, TFiT focused on four activity areas: collision risk, underwater noise, electromagnetic fields, and changes in habitat. Technologies and methodologies were tested at field sites in Alaska, Washington, California, and New Hampshire. Detailed information on the effectiveness of the identified methodologies and specific recommendations for each of the four focus areas are included in the companion papers in this Special Issue.

Introduction: During the COVID-19 lockdown significant improvements in urban air quality were detected due to the absence of motorized vehicles. It is crucial to perpetuate such improvements to maintain and improve public health simultaneously. Therefore, this exploratory study approached bicycle infrastructure in the case of Munich (Germany) to find out which specific bicycle lanes meet the demands of its users, how such infrastructure looks like, and which characteristics are potentially important. Methods: To identify patterns of bicycle infrastructure in Munich exploratory data is collected over the timespan of three consecutive weeks in August by a bicycle rider at different times of the day. We measure position, time, velocity, pulse, level of sound, temperature and humidity. In the next step, we qualitatively identified different segments and applied a cluster analysis to quantitatively describe those segments regarding the measured factors. The data allows us to identify which bicycle lanes have a particular set of measurements, indicating a favorable construction for bike riders. Results: In the exploratory dataset, five relevant segment clusters are identified: viscous, slow, inconsistent, accelerating, and best-performance. The segments that are identified as best-performance enable bicycle riders to travel efficiently and safely at amenable distances in urban areas. They are characterized by their width, little to no interaction with motorized traffic as well as pedestrians, and effective traffic light control. Discussion: We propose two levels of discussion: (1) revolves around what kind of bicycles lanes from the case study can help to increase bicycle usage in urban areas, while simultaneously improving public health and mitigating climate change challenges and (2) discussing the possibilities, limitations and necessary improvements of this kind of exploratory methodology.

Railways play an essential role in China’s development, driving economic and social progress while negatively impacting the environment. Assessing different railway projects’ sustainability can maximize the positive effects and minimize the side effects. This article aims to propose a methodological framework containing a series of indicators to evaluate the sustainability of four railway projects in China. A hybrid MCDM (multi-criteria decision-making) method was adopted to analyze the interrelationships among the dimensions and indicators and then present the projects’ differences. The weights of each indicator in the research were studied according to experts’ advice, and the same indicators were of different importance when placed in different research environments, such as developing and developed countries. This helps to establish a developing-country-centered evaluation indicator system. After comparison, it can be seen that Railway A is the best in terms of sustainability, mainly because it is in an economically developed region of China that is rich in construction resources, and is less constrained by natural conditions than other projects. The results show that although environmental sustainability has been improved over the past few years, its low level of influence still urges people to invest more attention and take more actions with significant effects in this respect. Furthermore, railways show significant differences in economic sustainability, while the differences in social sustainability have reduced considerably. This study provides further insight into the investigated measures and proposes recommendations for improving railway transport in China.

A survey data on European Consumers' adoption attitude towards electric vehicles (EVs), derived from an earlier research and its dataset posted under Mendeley Data under https://data.mendeley.com/datasets/85nz9k5tf5/4. Specifically, the new derived dataset in this repository is derived from “(6)_Transnational_EVsurvey_datavalues.csv” of the source data. The dataset consists of 69 predictor features and one binary target feature, which is Question 16 (Q16), which asks the adoption intention regarding EVs. The dataset is suitable for classification analysis, especially with continuization, as done in the research paper, yet can also be analyzed with association mining, as it contains many binary attributes. The Full Supplement also includes a presentation of the paper, the Orange *.ows model for classification and ranking analysis, and a Supplement document file that contains detailed Literature review.