Maria Clara Vaz

Abstract

Abstract
The transport sector plays a fundamental role in the European Union economy and its efficiency is fundamental to strengthen the region's environmental and economic performance. Unfortunately, the sector still remains heavily dependent on oil resources and is responsible for a large part of the air pollution. The European Union has been promoting various initiatives towards sustainable transport development by setting targets in the sector such as the ones proposed in the 2011 White Paper on transport. Under this context, this study aims at evaluating the environmental performance of the transport sector in 28 European Union countries, from 2015 to 2018, towards the policy agenda established in the strategic documents. The assessment of the transport environmental performance is made through the aggregation of seven sub-indicators into a composite indicator using a Data Envelopment Analysis technique. A variant of the Benefit of the Doubt model is used to determine the weights to aggregate the sub-indicators. The results obtained indicate that the European Union countries have been improving their transport environmental performance in the last two years of the time span under analysis, i.e., 2017 and 2018. Regarding the inefficient countries, results suggest they should improve the transport sustainability mainly by drastically reducing the greenhouse gas emissions from fossil fuel-based propulsion, increasing the share of freight transport using rail and inland waterways and also the share of transport energy from renewable sources.

Abstract

Abstract

Abstract
Predicting the performance of a mixture is crucial to designing experiences in product development and formulation research. In this work, an application, MDesign, is proposed to construct models in a mixture design with a practical, educational, and intuitive approach. Developed in MATLAB software, the standalone application aims to contribute to the study of mixtures through the definition of multivariate models of different orders, enabling their statistical analysis to verify the robustness of each of those models. Compared to the obtained results from other applications using data experiments published in the literature, the proposed application presents accurate results and good execution. MDesign can be considered an automatic, robust, and valuable tool to support the mixture design in an industrial context.