Neuronal Network Based Modelling of Demand and Competing use of Forestry Commodities for Material and Energy use

AbstractA methodology for development of scenarios for multiple forestry commodities quantities and prices through a nonlinear autoregressive neuronal network model with additional exogenous input parameters is presented. By mapping all possible interdependencies between forestry commodities and commodity prices, this approach shall enable to model the demand for different commodities and competing use for these commodities.The presented model performs good in terms of input-output correlation (R=0,99) for all variables combined. The results point to the conclusion that the functional relation between CO2-emission scenarios and biomass use can be captured by the modeling framework

Producing synthetic natural gas from microalgae via supercritical water gasification: A techno-economic sensitivity analysis

A techno-economic sensitivity analysis of the production of synthetic natural gas (SNG) via catalytic supercritical water gasification (SCWG) of microalgae produced in raceway ponds (RP), tubular-, or flat-panel-airlift photobioreactors (FPA-PBR) has been perfomed. The aim of combining microalgae production with SCWG is to close material flows with respect to water and nutrients, the so called SunCHem process. The sensitivity analysis is based on an annual production of 86,500 t of microalgae biomass yielding 1.14 PJ of methane per year. The sensitivity analysis showed that with an annual algae productivity of 38.5 t per hectare of RP an energy return on energy invested (EROEI) of 1.84 can be achieved for the self-sufficient base case scenario. An SNG production cost of 194 (sic) GJ (1) was obtained for RP. An EROEI of 0.08 was calculated for tubular PBR with a productivity of 75.1 t ha (-1) a(-1) in the base case scenario and thus was found to be inappropriate for SNG production. EROEI for FPA-PBR with an assumed microalgae productivity of 79 t ha (1) a (1) was found to be 1.01 in the base case scenario and an SNG production cost of 266 (sic) GJ (1). With significantly more optimistic assumptions concerning microalgae productivity, energy input and capital requirement with respect to microalgae cultivation, an EROEI of 3.6-5.8 and SNG production costs of 53-90 (sic) GJ (1) were found for RP, whereas for FPA-PBR an EROEI of 2-3.7 and SNG production costs of 30-103 (sic) GJ (1) were obtained. (C) 2013 Elsevier Ltd. All rights reserved

"Saferinternet" : eine explorative Studie zur Sichtweise von Eltern und Jugendlichen

Martina MatzenbergerKlagenfurt, Alpen-Adria-Univ., Dipl.-Arb., 2012(VLID)241161

International Journal of Disaster Resilience in the Built Environment

The purpose of this paper is to outline different notions of the term resilience used in scientific disciplines and consequently explore how the concept can be applied to energy systems. The concept of resilience has emerged recently in scientific discourse. The major questions to be addressed are: Which definitions and underlying concepts of resilience are used in the scientific literature? How can resilience be defined with respect to energy systems and which underlying principles can be identified

Validating daily social media macroscopes of emotions

To study emotions at the macroscopic level, affective scientists have made extensive use of sentiment analysis on social media text. However, this approach can suffer from a series of methodological issues with respect to sampling biases and measurement error. To date, it has not been validated if social media sentiment can measure the day to day temporal dynamics of emotions aggregated at the macro level of a whole online community. We ran a large-scale survey at an online newspaper to gather daily self-reports of affective states from its users and compare these with aggregated results of sentiment analysis of user discussions on the same online platform. Additionally, we preregistered a replication of our study using Twitter text as a macroscope of emotions for the same community. For both platforms, we find strong correlations between text analysis results and levels of self-reported emotions, as well as between inter-day changes of both measurements. We further show that a combination of supervised and unsupervised text analysis methods is the most accurate approach to measure emotion aggregates. We illustrate the application of such social media macroscopes when studying the association between the number of new COVID-19 cases and emotions, showing that the strength of associations is comparable when using survey data as when using social media data. Our findings indicate that macro level dynamics of affective states of users of an online platform can be tracked with social media text, complementing surveys when self-reported data is not available or difficult to gather

A novel approach to assess resilience of energy systems

The concept of resilience has emerged recently in scientific discourse. Different notions of the term resilience used in scientific disciplines are outlined and consequently explored with regard to how the concept can be applied to energy systems. The major questions to be addressed are: Which definitions and underlying concepts of resilience are used in the scientific literature? How can resilience be defined with respect to energy systems and which underlying principles can be identified? Building on this understanding characteristics of the resilience concept used in various contexts are described and a methodology for selection of an indicator set for an energy resilience assessment is presented. The methodology for a resilience assessment outlined in this paper requires definition and clustering of a set of indicators describing a resilient system. It contributes to understanding system properties and supports the theory of how to improve system resilience

A novel approach to assess resiliency of energy systems

The scope of this document is to outline different notions of the term resilience used in the scientific literature and explore how the concept of resilience can be applied to energy systems. Thus the major questions to be addressed are: Which definitions and underlying concepts of resilience are used in the scientific literature? How can resilience be defined with respect to energy systems and which underlying principles can be identified? Different characteristics of the resilience concept used in various contexts are outlined and a methodology for selection of an indicator set for an energy resilience assessment is presented. Definitions of resilience, vulnerability and adaptability are very much interlinked. A novel framework is proposed to foster the understanding of the interlinkage between these three terms and to cluster indicators to assess energy system resilience. It is argued that resilience can be defined as a function of vulnerability and adaptability, therefore increasing adaptability or reducing vulnerability causes higher system resilience

Development of a tool to model European biomass trade : Report for IEA Bioenergy Task 40

This report investigated the potential of future intra- and inter-European trade of solid biomass for bioenergy purposes taking country to country specific intermodal transport routes into account and matching supply and demand for energy crops, forestry products and residues and agricultural residues. For this purpose, a geospatial, intermodal biomass transport model was developed in the ArcGIS 10.0 Network Analyst extension. This model has been complemented with data on the cost of shipment using road (truck), water (ocean ships and inland navigation ships) and rail and the cost of transshipment between these modalities. The results of the ArcGIS model were integrated in the transport extended renewable energy model GREEN-X and combined with two scenarios on import potential scenarios of biomass from non-EU countries, a Low Import and High Import scenario. The approach applied provides useful insights in potential trade routes, key supply regions and key demand regions in Europe and potential cost implications for bioenergy production taking logistic implications of biomass from farm gate to supply destinations into account. Because biomass is becoming a major tradable energy commodity, representing bioenergy trade is of key importance to energy models that include renewable energy as no (European) country is limited to national resources