The growth of container transport places increasing demand on traffic, especially in situations where container terminals are located near the city centers. The main problem is traffic congestion on networks caused by the integration of Heavy-Duty Vehicles and urban traffic flows. The main objective is to identify the critical traffic parameters which cause negative organizational and environmental impacts on the existing and future traffic demand. A micro-level traffic simulation model was implemented for the testing of the proposed framework-based supply, demand, and control layers. The model was generated and calibrated based on the example of a mid-size Container Terminal “Brajdica” and the City of Rijeka, Croatia. The results indicate that the critical parameters are Queue Length on the approach road to the Container Terminal and the Stop Delay on the main city corridor. High values of these parameters cause negative effects on the environment because of increased fuel consumption and the generation of extra pollution. Due to this problem, a sensitivity analysis of the traffic system performance has been conducted, with a decrement of Terminal Gate Time distribution by 10%. After re-running simulations, the results indicate the impact of subsequent variation in Terminal Gate Time on the decrease of critical parameters, fuel consumption, and vehicle pollution.

The optimization of seaside operations at container terminals includes solving standard berth and crane allocation problems. The question arises about the efficiency of such optimizations in small and medium-sized container terminals, with different quay designs or different terminal layouts. This paper focuses on developing an integrated model that would apply to medium-sized terminals with a multi-quay layout. The main objectives are determining the shortest possible vessel stay at the port and providing a high-reliability service to ship operators. The developed integrated model includes the optimization process in three stages: initiation, assignment, and adjustment. The model’s main feature is generating operational scenarios based on the cargo distribution onboard and integrated berth and crane allocation. The aim is to choose the most favorable option to optimize ships’ overall processing time in the planning horizon. The experiment was conducted to test the model’s functionality and justify the results by comparing the results obtained by the integrated model with the classical approach of berth and crane allocation in a multi-quay environment. The results show significant improvements in peak periods when ships’ arrivals are concentrated in smaller time intervals by applying the integrated model.

As nautical tourism and recreational activities involving boats have become highly popular, research interest on various effects of nautical tourism is also increasing. This paper aims to analyze the main scientific contributions in the field of nautical tourism and its impact on the environment. The focus of the analysis is on the methods used to estimate and model recreational boating activities. Since nautical tourism plays a crucial role in the context of the growth and development of the economy, it is necessary to consider the environmental component of its development. The background objective of the paper is to provide a representation of environmental descriptors, i.e., to highlight in particular the environmental impact of nautical tourism. A search on the Web of Science Core Collection, touching on this topic, is composed of scientific papers published in the period 2010–2021. The papers examined are divided into five categories according to the impact of nautical tourism they study: Environmental, Economic, Social, Technical or Other. The results show that most papers were published in the area of environmental impacts of nautical tourism, with most papers examining invasive species, antifouling and impacts on species. The analysis showed that the negative impacts were mainly studied individually. Based on the analysis and evaluation of the scientific publications, a basic recommendation is given for the construction of a model to estimate recreational boating activities and its impact on the environment.

Nowadays, container terminals are subject to extensive technological changes and specific transformations. Changes applied to terminals tend to increase their ability to offer high- end personalized services to the customers and finally affect the competitiveness. The estimation of efficiency corresponds to terminals’ ability to increase the production with a specific level of inputs and has been the topic of many studies, especially those conducted on a wider regional or global level. The main objectives of our research are to evaluate the model, conduct sensitivity analysis, and estimate technical efficiencies on a sample of North Adriatic Ports Association (NAPA) interconnected medium-sized terminals, located in the narrow geographic area, on the same transport corridor thus representing each other’s competition. For that purpose, we have implemented a stochastic frontier approach on a balanced panel dataset of first-order and additionally introduced control input variables with Cobb-Douglas and trans-logarithmic functional forms. The stochastic production frontier estimation shows the range of NAPA terminals’ technical efficiencies from 65.24% to 93.92%, with a global average of 78.49% and a positive trend of 1.28% over the observed period of time. Our findings also indicate that NAPA terminals with the highest estimated technical efficiencies do not necessarily need to be the most productive ones, and vice versa.

The optimization of the goods delivery to Rijeka’s city center presents a complex organizational framework where many parameters must be taken into account and a diverse multi-methodological approach, needs to be utilized. The building of a distribution center is asserted here to be one notable way to improve the existing delivery service. The grouping of freight in a distribution center would result in a reduction of transport costs due to a smaller number of vehicles entering the city center, in turn reducing the traffic burden incumbent on the city’s transport network. In this paper, two of the many possible methods related to the optimization of goods delivery in city centers, have been used. Based on the data collected through the study’s questionnaire, conducted in the area of the city of Rijeka, the method of gravity center has been used to determine the location of the distribution center. Then, based on the tentative location of the distribution center, the method of optimization of the transport process has been applied by resorting to transport problem-solving methods, including several different implementation scenarios. From the proposed solutions, and based on the results detailed, the solution that was found to be the most credible was arguably the best match with the default criterion.

The growing demand for private and public transport services in urban areas requires sophisticated approaches to achieve satisfactory mobility standards in urban areas. Some of the main problems in urban areas today are road congestions and consequently vehicle emissions. The aim of this paper is to propose a methodological approach for the estimation of vehicle emissions. The proposed methodology is based on two interrelated models. The first model is a microscopic simulation SUMO model which can be used to identify the most congested urban areas and roads with critical values of traffic parameters. The second model is the COPERT Street Level for estimating vehicle emissions. The proposed models were tested on the urban area of Rijeka. The results of the microscopic SUMO simulation model indicate six urban roads with the critical traffic flow parameters. On the basis of the six identified urban roads, an estimation of vehicle emissions was carried out for specific time periods: 2017, 2020, 2025, and 2030. According to the results of the second model, the urban road R20-21 was identified as the most polluted road in the urban district of Rijeka. The results indicate that over the period 2017–2030, CO emissions will be reduced on average by 57% on all observed urban roads, CO2 emissions by 20%, and PM emissions by 58%, while the largest reduction of 65% will be in NOx emissions.