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- Environmental performance assessment of the transport sector in the European UnionPublication . Gruetzmacher, Sarah; Ferreira, Ângela P.; Vaz, Clara B.; Castagna, Annemarlen GehrkeThe transport sector plays a fundamental role in the European economy. Efficient transport services and infrastructure are fundamental for making the most of the region’s economic strengths. Unfortunately, the European Union transport sector still remains heavily dependent on oil resources and, therefore, it is responsible for a large part of the air pollution. The emissions from the sector have reduced in the last decade, but not enough to limit its impact on the environment and climate. Reducing its pressure on the environment is critical to achieve long-term sustainability. The European Union has been promoting diverse initiatives towards sustainable transport development and environment protection by setting targets for changes in the sector as the ones proposed in 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 was made through the aggregation of seven sub-indicators into a composite indicator using a Data Envelopment Analysis approach. Two models were first used to determine the weights to aggregate the subindicators: the conventional Benefit of the Doubt model and a variant of the model, both with virtual proportional weights restrictions. The results indicate that the European Union countries have been improving their transport environmental performance in the last two years analysed, 2017 and 2018. The inefficient countries should improve the transport sustainability mainly by drastically reducing the greenhouse gas emissions from fossil fuel, increasing the share of freight transport that uses rail and inland waterways and also the share of transport energy from renewable sources.
- A panel data analysis of the electric mobility deployment in the Eropean UnionPublication . Gruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P.This study aims to find and develop an appropriate optimization approach to reduce the time and labor employed throughout a given chemical process and could be decisive for quality management. In this context, this work presents a comparative study of two optimization approaches using real experimental data from the chemical engineering area, reported in a previous study [4].The first approach is based on the traditional response surface method and the second approach combines the response surface method with genetic algorithm and data mining. The main objective is to optimize the surface function based on three variables using hybrid genetic algorithms combined with cluster analysis to reduce the number of experiments and to find the closest value to the optimum within the established restrictions. The proposed strategy has proven to be promising since the optimal value was achieved without going through derivability unlike conventional methods, and fewer experiments were required to find the optimal solution in comparison to the previous work using the traditional response surface method.
- Assessment of the transport sustainability performance in the European UnionPublication . Gruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P.The transport sector plays a fundamental role in the European economy. By 2017, the transport sector employed directly more than 11 million people, around 57c of the total workforce, and its activities accounted for about 5% of Europe's Gross Domestic Product (GDP). Promoting efficient transport services and infrastructure is fundamental for making the most of the European's economic strengths, supporting the internal market and its growth. Unfortunately, the European Union transport sector still remains heavily dependent on oil resources and, therefore, it is responsible for a large part of the air pollution. The emissions from the sector have reduced in the last decade, but not enough to limit its impact on the environment and climate. Reducing its pressure on the environment is critical to achieve long-term sustainability. The European Union has been promoting diverse initiatives to- wards sustainable transport development and environment protection by setting targets for changes in the sector, as those proposed in the 2011 White Paper on transport [1]. This study aims at evaluating the sustainable performance of the transport sector in the 28 European Union countries, from 2015 to 2017, towards the policy agenda established in strategic documents. The assessment of the transport environmental performance was made through the aggregation of seven sub-indicators into a compos- ite indicator using a Data Envelopment Analysis approach. The model used to determine the weights to aggregate the sub-indicators is based on a variant of the Benefit of the Doubt model with virtual proportional weights restrictions as proposed by Färe et a1. [2] . The results indicate that, overall, the European Union countries had almost no variation on its transport environmental performance during the time span under analysis. The inefficient countries can improve the transport sustainability mainly by drastically reducing the greenhouse gas emissions from fossil fuels combustion, increasing the share of freight transport that uses rail and waterways and also the share of transport energy from renewable sources.
- Sustainability performance assessment of the transport sector in European countriesPublication . Gruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P.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.
- Environmental performance assessment of the transport sector in the European UnionPublication . Gruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P.Reducing the European Union (EU) transport sector’s pressure on the environment is critical to achieve long-term sustainability. This study evaluates the environmental performance of the transport sector in 28 EU countries, from 2015 to 2017, towards a more sustainable mobility by using composite indicators (CI). The assessment was made through the aggregation of 7 sub-indicators into a CI using a DEA approach. The results indicate that the EU countries had almost no variation on their transport environmental performance in these 3 years analyzed.
- A panel data analysis of the electric mobility deployment in the European UnionPublication . Gruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P.Governments all over the world have been promoting electric mobility as an effort to reduce the transport sector’s greenhouse emissions and fossil fuel dependency. This work analyses the deployment of electric vehicles in the European Union countries, between 2015 and 2019, and the variables that may influence it, using a panel data methodology. The present work focuses on the deployment of battery and plug-in hybrid electric vehicles, individually and jointly. Nine explanatory variables were included in the model: density of recharging points, gross domestic product per capita, cumulative number of policies on electromobility, share of renewable energy in transport, total greenhouse gas emissions per capita, tertiary education attainment, electricity price, employment rate and new registrations of passenger cars per capita. The results showed that the indicators influence differently the deployment of the different types of electric vehicles. The most significant factor driving the battery electric vehicles deployment was the density of recharging points, while for plug-in hybrid electric vehicles was the share of renewable energy. Policy makers should focus on adjusting actions to the demand for the different types of electric vehicles.
- Assessing the deployment of electric mobility: a reviewPublication . Gruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P.The transport sector of the European Union is the only sector of the economy that has been increasing its emissions since 2014. To reduce the use of fossil fuels and achieve the greenhouse gas emissions mitigation target, many countries are focusing on the deployment of electric vehicles. This paper aims at analysing recent literature on the deployment of electric vehicles (EV) and typifying objectives, methods and indicators generally exploited, to better understand the state of the art on this topic. The Web of Science database was used and the results showed that the interest in the topic of electric vehicles has been increasing exponentially since 2010. The main significant indicators and the assessment methodologies were analysed. The indicators identified were aggregated in four main clusters: environmental, economic, social and technical indicators. Although the factors that contribute to EV deployment can vary depending on the regions specific characteristics, most of the research studies pointed out that the main contributors are the high density of recharging points, the existence of government monetary incentives and the lower operational cost of EV.
- Environmental performance assessment of the transport sector in the european unionPublication . Gruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P.The European Union (EU) has been promoting diverse initiatives towards sustainable development and environment protection. One of these initiatives is the reduction of the greenhouse gas (GHG) emissions in 60% below their 1990 level, by 2050. As the transport sector is responsible for more than 22% of those emissions some strategies need to be taken towards a more sustainable mobility, as the ones proposed in 2011 White Paper on transport. Under this context, this study aims to evaluate the environmental performance of the transport sector in the 28 EU countries towards these goals, from 2015 to 2017. The transport environmental performance is measured through the composite indicator derived from the Benefit of the Doubt (BoD) model. The country transport environmental performance is assessed through the aggregation of multiple sub-indicators using the composite indicator derived from the Data Envelopment Analysis (DEA) model. The results indicate that the EU countries slightly improved their transport environmental performance, on average 2.8%. The areas where the inefficient countries need more improvement were also identified: reducing the GHG emissions from fossil fuels, increasing the share of transport energy from renewable sources and improving the public transport share of the total passenger transport.
- Performance assessment of the transport sustainability in the European UnionPublication . Gruetzmacher, Sarah; Vaz, Clara B.; Ferreira, Ângela P.Based in the current growth rate of metropolitan areas, providing infrastructures and services to allow the safe, quick and sustainable mobility of people and goods, is increasingly challenging. The European Union has been promoting diverse initiatives towards sustainable transport development and environment protection by setting targets for changes in the sector, as those proposed in the 2011 White Paper on transport. Under this context, this study aims at evaluating the environmental performance of the transport sector in the 28 European Union countries, from 2015 to 2017, towards the policy agenda established in strategic documents. The assessment of the transport environmental performance was made through the aggregation of seven sub-indicators into a composite indicator using a Data Envelopment Analysis approach. The model used to determine the weights to aggregate the sub-indicators is based on a variant of the Bene t of the Doubt model with virtual proportional weights restrictions. The results indicate that, overall, the European Union countries had almost no variation on its transport environmental performance during the time span under analysis. The ine cient countries can improve the transport sustainability mainly by drastically reducing the greenhouse gas emissions from fossil fuels combustion, increasing the share of freight transport that uses rail and waterways and also the share of transport energy from renewable sources.
- COVID-19 time series predictionPublication . Oliveira, Leonardo Sestrem de; Gruetzmacher, Sarah; Teixeira, João PauloThe Artificial Neural Network (ANN) is a computer technique that uses a mathematical model to represent a simpler form of the biologic neural structure. It is formed by many processing units and its intelligent behavior comes from the iterations between these units. One application of the ANN is for time series prediction algorithms, where the network learns the behavior of time dependent data and it is able to predict future values. In this work, the ANN is applied in predicting the number of COVID-19 confirmed cases and deaths and also the future seven days for the time series of Brazil, Portugal and the United States. From the simulations it is possible to conclude that the prediction of confirmed cases and deaths from COVID-19 have been successfully made by the ANN. Overall, the ANN with a specific test set had a Mean Squared Error (MSE) 50% higher than the ANN with a random test set. The combination of the sigmoidal and linear activation functions and the Levenberg-Marquardt training function had the lowest MSE for all cases