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Gas chromatography (GC) is an excellent tool to obtain qualitative and quantitative information on volatile organic compounds (VOCs) present in gaseous samples. However, to carry out an appropriate quantitative analysis of unknown samples, the use of known concentration gas mixtures, to exploit as standards, is required. Commonly, these mixtures are obtained from cylinders of compressed gas at known concentrations: this involves a considerable economic outlay and problems relating to their handling. This paper aims to apply a method, proposed as a versatile, simple, and economical alternative to the use of such cylinders, for preparing gaseous calibration standards useful to obtain calibration curves for quantification of air pollutants. In addition, the operative limits of this method were investigated. The method involves the continuous injection of volatile compounds in liquid form into a stream of neutral gas, such as air or nitrogen. Exploiting the high volatility of the compounds used, it is possible to generate a continuous gas stream containing the chosen VOC at the desired concentration based on the mass balance of the system. This method proved to be suitable for compounds with volatility ranging from 36 kPa to 0.1 kPa at 293 K and it showed relative bias and relative standard deviation (RSD) values of less than 16% and 8%, respectively. The described dynamic method results are repeatable and accurate. It can be used effectively for compounds with vapour pressure values within the stated limits and provides a more versatile and cost-effective alternative to compressed gas cylinders.

Gas chromatography (GC) is an excellent tool to obtain qualitative and quantitative information on volatile organic compounds (VOCs) present in gaseous samples. However, to carry out an appropriate quantitative analysis of unknown samples, the use of known concentration gas mixtures, to exploit as standards, is required. Commonly, these mixtures are obtained from cylinders of compressed gas at known concentrations: this involves a considerable economic outlay and problems relating to their handling. This paper aims to apply a method, proposed as a versatile, simple, and economical alternative to the use of such cylinders, for preparing gaseous calibration standards useful to obtain calibration curves for quantification of air pollutants. In addition, the operative limits of this method were investigated. The method involves the continuous injection of volatile compounds in liquid form into a stream of neutral gas, such as air or nitrogen. Exploiting the high volatility of the compounds used, it is possible to generate a continuous gas stream containing the chosen VOC at the desired concentration based on the mass balance of the system. This method proved to be suitable for compounds with volatility ranging from 36 kPa to 0.1 kPa at 293 K and it showed relative bias and relative standard deviation (RSD) values of less than 16% and 8%, respectively. The described dynamic method results are repeatable and accurate. It can be used effectively for compounds with vapour pressure values within the stated limits and provides a more versatile and cost-effective alternative to compressed gas cylinders.

Electric vehicles require sufficient public charging infrastructure. This in turn necessitates detailed information on charging demand. In this paper we present a four-step approach to estimating public charging demand of electric vehicles. Previous methods are limited in their ability to provide differentiated results and adapt to future developments. Therefore, we account for user groups (private, carsharing, commercial), technical developments (vehicles, infrastructure), infrastructure availability, and carsharing development (operational area, business models, autonomous vehicles). Our approach also considers the interactions between these factors and allows for scenario analysis yielding the quantity and spatial distribution of public charging demand. We demonstrate our approach for Berlin, Germany. We find that the majority of public charging demand results from carsharing. This demand is concentrated in the city center, even when carsharing is available citywide. Public charging demand for commercial users is relatively low and located outside the city center. For private users, public charging demand shifts to the city center with an increasing market penetration of electric vehicles and technological advancements (increased range, charging speed). Public demand from private users increases dramatically when private infrastructure is absent. Finally, public charging demand shifts to the city center when private users do not have private infrastructure.

Electric vehicles require sufficient public charging infrastructure. This in turn necessitates detailed information on charging demand. In this paper we present a four-step approach to estimating public charging demand of electric vehicles. Previous methods are limited in their ability to provide differentiated results and adapt to future developments. Therefore, we account for user groups (private, carsharing, commercial), technical developments (vehicles, infrastructure), infrastructure availability, and carsharing development (operational area, business models, autonomous vehicles). Our approach also considers the interactions between these factors and allows for scenario analysis yielding the quantity and spatial distribution of public charging demand. We demonstrate our approach for Berlin, Germany. We find that the majority of public charging demand results from carsharing. This demand is concentrated in the city center, even when carsharing is available citywide. Public charging demand for commercial users is relatively low and located outside the city center. For private users, public charging demand shifts to the city center with an increasing market penetration of electric vehicles and technological advancements (increased range, charging speed). Public demand from private users increases dramatically when private infrastructure is absent. Finally, public charging demand shifts to the city center when private users do not have private infrastructure.

The remarkable growth of distributed generation (DG) penetration inside electrical power systems turns the familiar passive distribution networks (PDNs) into active distribution networks (ADNs). Based on the backward/forward sweep method (BFS), a new power-flow algorithm was developed in this paper. The algorithm is flexible to handle the bidirectional flow of power that characterizes the modern ADNs. Models of the commonly used distribution network components were integrated with the developed algorithm to form a comprehensive tool. This tool is valid for modeling either balanced or unbalanced ADNs with an unlimited number of nodes or laterals. The integrated models involve modeling of distribution lines, losses inside distribution transformers, automatic voltage regulators (AVRs), DG units, shunt capacitor banks (SCBs) and different load models. To verify its validity, the presented algorithm was first applied to the unbalanced IEEE 37-node standard feeder in both passive and active states. Moreover, the algorithm was then applied to a balanced 22 kV real distribution network as a case study. The selected network is located in a remote area in the western desert of Upper Egypt, far away from the Egyptian unified national grid. Accordingly, the paper examines the current and future situation of the Egyptian electricity market. Comparison studies between the performance of the proposed ADNs and the classical PDNs are discussed. Simulation results are presented to demonstrate the effectiveness of the proposed ADNs in preserving the network assets, improving the system performance and minimizing the power losses.

The remarkable growth of distributed generation (DG) penetration inside electrical power systems turns the familiar passive distribution networks (PDNs) into active distribution networks (ADNs). Based on the backward/forward sweep method (BFS), a new power-flow algorithm was developed in this paper. The algorithm is flexible to handle the bidirectional flow of power that characterizes the modern ADNs. Models of the commonly used distribution network components were integrated with the developed algorithm to form a comprehensive tool. This tool is valid for modeling either balanced or unbalanced ADNs with an unlimited number of nodes or laterals. The integrated models involve modeling of distribution lines, losses inside distribution transformers, automatic voltage regulators (AVRs), DG units, shunt capacitor banks (SCBs) and different load models. To verify its validity, the presented algorithm was first applied to the unbalanced IEEE 37-node standard feeder in both passive and active states. Moreover, the algorithm was then applied to a balanced 22 kV real distribution network as a case study. The selected network is located in a remote area in the western desert of Upper Egypt, far away from the Egyptian unified national grid. Accordingly, the paper examines the current and future situation of the Egyptian electricity market. Comparison studies between the performance of the proposed ADNs and the classical PDNs are discussed. Simulation results are presented to demonstrate the effectiveness of the proposed ADNs in preserving the network assets, improving the system performance and minimizing the power losses.

The city’s built environment and functionality play a crucial role in shaping individual mobility patterns, impacting the overall health and quality of life of its population. Understanding these influences is an important research topic, making it a central focus of this paper. This study aims to identify the factors responsible for promoting healthy mobility behavior. To address this comprehensively, a multidisciplinary empirical survey was developed based on the “Triad”—a model consisting of the built environment, mobility(-behavior), and public health. In addition to the evaluation of socio-demographic factors and activity radius mapping, statistical analyses like multiple linear regression were used. These statistical analyses allow the assessment of the impact of various independent variables on the promotion of healthy mobility behavior within urban settings. The multiple regression shows that the satisfaction with the accessibility of public transport and the sense of safety as a cyclist contribute to explaining the variation of healthy mobility. Furthermore, the satisfaction with walking in the neighborhood and the inhalation of exhaust fumes while walking also seem to have an impact. The results show the link between the Triad and make it clear that mobility planning and urban planning must take a more integrated approach to promote health and simultaneously protect the climate.