1,146 research outputs found
System Level Life Cycle Assessment Models for EU and National Waste Management
No full textGlobal production and consumption has increased dramatically in recent decades and waste is currently being generated faster than any other environmental pollutant (Hoornweg et al., 2013). This has led world leaders to embrace the concept of a circular economy, where the ‘end-of-life’ concept is replaced with ‘restoration’ (Ellen MacArthur Foundation, 2020). The EU has thus, established a range of regulatory targets that prioritize the recycling and reuse of resources over incineration and landfill (European Commission, ND). This will inevitably lead to a wide range of new technological developments and product design requirements etc., to accommodate these targets. However, if waste is mismanaged, it can have detrimental consequences on both human health and the environment (Taelman et al., 2018). Thus, it is imperative that the impacts of waste management systems are assessed to ensure resource circularity whilst avoiding any adverse effects. In addition, it is important to assess whether or not the regulatory targets are aimed at the appropriate waste streams and sectors. Currently, no studies provide a comprehensive and system level life cycle assessment (LCA) model that enables consistent assessment of all of the waste streams occurring at national or regional level. This study, therefore, contributes to an ongoing EU project that seeks to develop a flexible modelling framework, which is adaptable to changes in framework conditions, technology options and regulatory focus etc., for quantification of relevant impacts on the EU waste management system, with particular focus on addressing future changes, tracking material flows, uncertainty analysis, and on import of EU and country-specific waste data through Eurostat. At the conference, the current model set-up along with any preliminary results and ongoing recommendations are presented. References Hoornweg, D., Bhada-Tata, P., and Kennedy, C. (2013). Environment: Waste Production Must Peak This Century. Nature, v. 502, pages 615-617. https://doi.org/10.1038/502615a. Ellen MacArthur Foundation (2020). ‘It’s time to step up, not step back’ – more than 50 global leaders pledge to build back better with the circular economy. Retrieved from: https://www.ellenmacarthurfoundation.org/news/more-than-50-global-leaders-pledge-to-build-back-better-withthe- circular-economy. European Commission (ND). Waste and Recycling. Retreived from: https://ec.europa.eu/environment/topics/waste-and-recycling_en. Taelman, S. E., Tonini, D., Wandl, A., Dewulf, J. (2018). A Holistic Sustainability Framework for Waste Management in European Cities: Concept Development. Sustainability, 10(7), 1 33. https://doi.org/10.3390/su1007218
Clinical- vs. model-based selection of patients suspected of sepsis for direct-from-blood rapid diagnostics in the emergency department: a retrospective study
No full textSelecting high-risk patients may improve the cost-effectiveness of rapid diagnostics. Our objective was to assess whether model-based selection or clinical selection is better for selecting high-risk patients with a high rate of bacteremia and/or DNAemia. This study involved a model-based, retrospective selection of patients from a cohort from which clinicians selected high-risk patients for rapid direct-from-blood diagnostic testing. Patients were included if they were suspected of sepsis and had blood cultures ordered at the emergency department. Patients were selected by the model by adding those with the highest probability of bacteremia until the number of high-risk patients selected by clinicians was reached. The primary outcome was bacteremia rate. Secondary outcomes were DNAemia rate, and 30-day mortality. Data were collected for 1395 blood cultures. Following exclusion, 1142 patients were included in the analysis. In each high-risk group, 220/1142 were selected, where 55 were selected both by clinicians and the model. For the remaining 165 in each group, the model selected for a higher bacteremia rate (74/165, 44.8% vs. 45/165, 27.3%, p = 0.001), and a higher 30-day mortality (49/165, 29.7% vs. 19/165, 11.5%, p = 0.00004) than the clinically selected group. The model outperformed clinicians in selecting patients with a high rate of bacteremia. Using such a model for risk stratification may contribute towards closing the gap in cost between rapid and culture-based diagnostics
Design and characterisation of a stiff load cell with high overload capability and direct frequency output
No full text
Approaches for estimating stand-level volume using terrestrial laser scanning in a single-scan mode
No full textThe most efficient way to obtain stand inventory data with terrestrial laser systems (TLS) is with the single-scan mode, which involves taking one scan at a single point. With a single-scan setup, there will be a nondetection of trees in a plot and the representation of the individual trees will be incomplete. We explore how stand-level volume estimates, based on the single-scan mode, perform compared with standard inventory estimates. We base our study on 166 plots in 12 mature stands dominated by Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies L. Karst) in southern Norway. First, we compare individual-tree volume estimates from TLS with estimates from volume functions and measurements from harvesters. We show that individual-tree volumes can be estimated with high precision and accuracy with TLS in single-scan mode. Secondly, we test three approaches for correction of nondetection relying on model-based estimates of the detection probability obtained by point transect sampling estimators. We show that all three approaches adjust for nondetection and yield stand-level volume estimates that are similar to those obtained by fixed-area sampling. In conclusion, our results indicate that stand-level volume estimates, based on single-scan mode TLS data, perform well compared with standard inventory estimates.BALABU [192263]; Norwegian Research Counci
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