Abstract
The volatile organic compounds benzene, toluene, ethylbenzene, and xylene (BTEX) are emitted into the atmosphere at gas stations (GS) leading to chronic exposure of nearby residents, which raises public health concerns. This study aimes at determining the contribution of GS emissions to BTEX exposure in nearby residents. Three Control and Exposed areas to BTEX emissions from GS were defined in a medium-sized European city (Porto, Portugal). BTEX atmospheric levels were determined in Control and Exposed areas using passive samplers deployed outdoors (n = 48) and indoors (n = 36), and human exposure was estimated for 119 non-smoking residents using the first urine of the day. Results showed that median BTEX outdoor and indoor concentrations were significantly higher for Exposed than Control areas, with exception of ethylbenzene and xylene indoor concentrations, where no marked differences were found. Comparison of urinary concentrations between Exposed and Control residents demonstrated no significant differences for benzene and ethylbenzene, whereas levels of toluene and xylene were significantly higher in Exposed residents. No marked correlation was obtained between atmospheric BTEX concentrations and urinary concentrations. Data indicate the potential impact on air quality of BTEX emissions from GS, which confirms the importance of these findings in urban planning in order to minimize the impact on health and well-being of surrounding populations.

Abstract
Diesel-fueled buses have been replaced by Compressed Natural Gas (CNG) to minimize the high level of emissions in urban areas. However, differences in indoor exposure levels to Benzene, Toluene, Ethylbenzene and Xylene (BTEX) in those vehicles have not been investigated so far. The primary aim of this study was to determine if passengers are exposed to different BTEX levels when using buses powered by CNG or by diesel, and further explore if indoor levels are influenced by external air quality. For this purpose, BTEX air concentrations were measured in bus cabins (CNG and diesel), parking stations and in a background urban area using passive air samplers. Results showed that BTEX concentrations inside vehicles were higher than outside, but no significant differences were found between buses powered by CNG or by diesel. In CNG vehicles, high and significant positive correlation was found between benzene and the number of journeys in the same route (r(s) = 0.786, p < 0.05), vehicle operating time (r(s) = 0.738, p < 0.05), exposure time (r(s) = 0.714, p < 0.05) and exposure index (r(s) = 0.738, p < 0.05), but this was not observed for diesel vehicles. Benzene in bus cabins was found to be significantly below reference value for human health protection. However, excepting p-xylene, all other aromatic pollutants have a mean concentration significantly above the lowest effect level (p <= 0.002 for all comparisons). Additionally, higher BTEX levels in cabin buses than in outdoor air suggest the presence of other emission sources in indoor cabins. These findings emphasize the need for further studies to fully characterize indoor emission sources in order to minimize the negative impact of BTEX exposure to human health.

Abstract
Jet impingement is widely implemented in a variety of engineering applications and industrial processes where high average heat transfer coefficients and the uniformity of the heat transfer over the impinging surface are required to enhance the process and to avoid local hot (or cold) spots. Multiple jet impingement involves several parameters that interfere with the performance of the process, and there are no universal optimal solutions. To ensure the optimization of the process, it is important to understand the influence of these parameters in the heat transfer over the target surface. To perform this study an experimental research will be performed on a purpose-built test facility which has been commissioned, using a Particle Image Velocimetry system. However, to reduce time and costs associated to the experimental tests, it is important to perform a Design of Experiments, that allows to reduce the number of trials, focusing on the parameters that have a greater influence on the process performance. Taguchi’s method allows the optimization of the process through the selection of the most suitable parameters values. This work presents the method that must be followed before the development of experiments related to the multiple jet impingement over a complex surface, from the design of the experimental setup to the design of the matrix of experiments. © 2019, Springer Nature Switzerland AG.

Abstract
This work proposes a mathematical programming model for jointly scheduling of production and transport in flexible manufacturing systems considering alternative job routing. Although production scheduling and transport scheduling have been vastly researched, most of the works address them independently. In addition, the few that consider their simultaneous scheduling assume job routes as an input, i.e., the machine -operation allocation is previously determined. However, in flexible manufacturing systems, this is an important source of flexibility that should not be ignored. The results show the model efficiency in solving small -sized instances.

Abstract
This work proposes a biased random key genetic algorithm (BRKGA) for the integrated scheduling of manufacturing, transport, and storage/retrieval operations in flexible manufacturing systems (FMSs). Only recently, research on this problem has been reported; however, no heuristic approaches have yet been reported. The computational results show the BRKGA to be capable of finding good quality solutions quickly.

Abstract
This work proposes an integrated formulation for the joint production and transportation scheduling problem in flexible manufacturing environments. In this type of systems, parts (jobs) need to be moved around as the production operations required involve different machines. The transportation of the parts is typically done by a limited number of Automatic Guided Vehicles (AGVs). Therefore, machine scheduling and AGV scheduling are two interrelated problems that need to be addressed simultaneously. The joint production and transportation scheduling problem is formulated as a novel mixed integer linear programming model. The modeling approach proposed makes use of two sets of chained decisions, one for the machine and another for the AGVs, which are inter-connected through the completion time constraints both for machine operations and transportation tasks. The computational experiments on benchmark problem instances using a commercial software (Gurobi) show the efficiency of the modeling approach in finding optimal solutions.