Global Resources Use and Pollution:Vol. I, Production, Consumption and Trade (1995-2008)

In the recent decades, the increase in the world population, the economic expansion and the globalization of the economy have led to a dramatic growth in the use of some natural resources and in the levels of pollution. These trends have coincided with a growing concern about some critical questions for the future of humankind such as resource scarcity and depletion, climate change, environmental degradation, the limits of growth or the inequalities in the access to natural resources across countries. In this context arises the need to develop a comprehensive dataset of reliable and comparable economic and environmental information that contributes to a better understanding of the complexity of these issues, and supporting evidence-based policy-making. In order to comply with this need, this Pocketbook presents a series of indicators describing the evolution of the use of natural resources and the emission of air pollutants around the world, in relation to production, consumption and trade activities. Based on different analysis derived from the World Input-Output Database (WIOD), this publication includes information on 6 environmental dimensions: land use, material extraction, water use, and emission of acid substances, greenhouse gases and ozone precursors. The time frame covered is the period between 1995 and 2008, and the geographical scope includes the EU-27 Member States, Brazil, China, India, Japan, Russia, the United States of America and the Rest of the World.JRC.J.5-Sustainable Production and Consumptio

Exploracion cardiovascular del feto

Centro de Informacion y Documentacion Cientifica (CINDOC). C/Joaquin Costa, 22. 28002 Madrid. SPAIN / CINDOC - Centro de Informaciòn y Documentaciòn CientìficaSIGLEESSpai

Comparing the use of GTAP-MRIO and WIOD for carbon footprint analysis

In this paper we explore the use of two different global multiregional input-output databases (GTAP-MRIO and WIOD) for the calculation of the global carbon emissions embodied in the final demand of nations (carbon footprint). We start our analysis with a description of the main characteristics of the databases and comparing their main components. Then, we calculate the carbon footprint with both databases and identify (from a global perspective) the most relevant factors underlying the resulting differences using structural decomposition analysis. The main conclusion that can be drawn is that, on average, certain elements of both databases can be said to be similar in around 75% to 80%, being only a few elements in each table the main drivers of the major differences. The divergences in the datasets of four countries explain almost 50% of the differences in the carbon footprint (USA 19.7%, China 18.1%, Russia 6.4% and India 4.3%). Industry wise, 50% of the differences can be explained by the divergences in three industries: (electricity 32.7%, refining 9.9% and inland transport 7.1%).JRC.J.5-Sustainable Production and Consumptio

Measuring the intra-EU employment driven by the EU exports to the rest of the world

Ensuring that comprehensive, reliable and comparable economic information is available to support evidence-based policymaking is crucial.The main motivation of this chapter is to show a tool to provide scientific evidence of the effects of international trade by means of multi regional Input-Output analysis.JRC.J.5-Sustainable Production and Consumptio

The Single Market as an Engine for Employment through External Trade

This article quantifies for the first time not only the domestic employment effects of foreign EU exports but also the correct number of jobs generated through intra-European trade (Single Market) in the production of such exported commodities. The literature has neglected very often the latter effects mainly due to the lack of an appropriate methodology and database. The empirical evidence shows that the EU has really progressed during the period 2000-2007 towards a more vertically integrated economy, reducing the labour intensity of the goods and services exported outside the EU, trading most prominently within the EU Single Market and subsequently, generating an increasing number of jobs. Despite the reduction in the labour intensity of the European exports, the associated employment grew from 22 to 25 million jobs, out of which 9 million jobs were created due to spillover and feedback effects associated to the Single Market.JRC.J.5-Sustainable Production and Consumptio

Global Resources Use and Pollution: Vol. II, Country Factsheets

In the recent decades, the increase in the world population, the economic expansion and the globalization of the economy have led to a dramatic growth in the use of some natural resources and in the levels of pollution. These trends have coincided with a growing concern about some critical questions for the future of humankind such as resource scarcity and depletion, climate change, environmental degradation, the limits of growth or the inequalities in the access to natural resources across countries. In this context arises the need to develop a comprehensive dataset of reliable and comparable economic and environmental information that contributes to a better understanding of the complexity of these issues, and supporting evidence-based policy-making. In order to comply with this need, this Pocketbook presents a series of indicators describing the evolution of the use of natural resources and the emission of air pollutants around the world, in relation to production, consumption and trade activities. Based on different analysis derived from the World Input-Output Database (WIOD), this publication includes information on 6 environmental dimensions: land use, material extraction, water use, and emission of acid substances, greenhouse gases and ozone precursors. The time frame covered is the period between 1995 and 2008, and the geographical scope includes the EU-27 Member States, Brazil, China, India, Japan, Russia, the United States of America and the Rest of the World. This volume II presents a series of factsheets with the main results by country for the years 1995 and 2008, and a comparison with the figures of the EU-27 for 2008 (for the EU Member States) or with those of the World.JRC.J.5-Sustainable Production and Consumptio

Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation

In this paper, a set of best practice data sharing guidelines for wind turbine fault detection model evaluation is developed, which can help practitioners overcome the main challenges of digitalisation. Digitalisation is one of the key drivers for reducing costs and risks over the whole wind energy project life cycle. One of the largest challenges in successfully implementing digitalisation is the lack of data sharing and collaboration between organisations in the sector. In order to overcome this challenge, a new collaboration framework called WeDoWind was developed in recent work. The main innovation of this framework is the way it creates tangible incentives to motivate and empower different types of people from all over the world to share data and knowledge in practice. In this present paper, the challenges related to comparing and evaluating different SCADA-data-based wind turbine fault detection models are investigated by carrying out a new case study, the “WinJi Gearbox Fault Detection Challenge”, based on the WeDoWind framework. A total of six new solutions were submitted to the challenge, and a comparison and evaluation of the results show that, in general, some of the approaches (Particle Swarm Optimisation algorithm for constructing health indicators, performance monitoring using Deep Neural Networks, Combined Ward Hierarchical Clustering and Novelty Detection with Local Outlier Factor and Time-to-failure prediction using Random Forest Regression) appear to exhibit high potential to reach the goals of the Challenge. However, there are a number of concrete things that would have to have been done by the Challenge providers and the Challenge moderators in order to ensure success. This includes enabling access to more details of the different failure types, access to multiple data sets from more wind turbines experiencing gearbox failure, provision of a model or rule relating fault detection times or a remaining useful lifetime to the estimated costs for repairs, replacements and inspections, provision of a clear strategy for training and test periods in advance, as well as provision of a pre-defined template or requirements for the results. These learning outcomes are used directly to define a set of best practice data sharing guidelines for wind turbine fault detection model evaluation. The guidelines can be used by researchers in the sector in order to improve model evaluation and data sharing in the future

Q Fever Outbreak among Workers at a Waste-Sorting Plant.

An outbreak of Q fever occurred in February-April 2014 among workers at a waste-sorting plant in Bilbao (Spain). The outbreak affected 58.5% of investigated employees, 47.2% as confirmed cases (PCR and/or serology) and 11.3% as probable cases (symptoms without laboratory confirmation). Only employees who had no-access to the waste processing areas of the plant were not affected and incidence of infection was significantly higher among workers not using respiratory protection masks. Detection by qPCR of Coxiella burnetii in dust collected from surfaces of the plant facilities confirmed exposure of workers inside the plant. Animal remains sporadically detected among the residues received for waste-sorting were the most probable source of infection. After cleaning and disinfection, all environmental samples tested negative. Personal protection measures were reinforced and made compulsory for the staff and actions were taken to raise farmers' awareness of the biological risk of discharging animal carcasses as urban waste

Estimated exposure date for Q fever infected workers.

<p>An incubation period of 2 weeks (crosses) or 4 weeks (squares) has been considered.</p