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A systemic framework of energy efficiency in schools: Experiences from six European countries
(2023)
Schools are complex physical and social institutions within national education systems. They account for significant energy consumption and like other buildings can demonstrate inefficient patterns of energy use. Poor energy performance of educational facilities is an intricate issue driven by complex causality of interconnected and dynamic factors. Addressing this issue requires a systemic approach, which is heretofore lacking. The aim of this research is to present and describe a systemic framework to facilitate energy reduction in schools across different European contexts. This transdisciplinary approach to sustainable energy use has been piloted in 13 post-primary schools located in six countries in northwest Europe. The research implements a series of planned activities and interventions, which help to unveil a systemic approach to improving energy efficiency in schools. The findings demonstrate how this approach, together with its ensuing methodologies and strategies, can contribute to reducing carbon emissions and improve knowledge and awareness around sustainable energy.
One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate "the problem of loosening a connection and the distribution of the work" as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.
The current work investigates the capability of a tailored multivariate curve resolution–alternating least squares (MCR-ALS) algorithm to analyse glucose, phosphate, ammonium and acetate dynamics simultaneously in an E. coli BL21 fed-batch fermentation. The high-cell-density (HCDC) process is monitored by ex situ online attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy and several in situ online process sensors. This approach efficiently utilises automatically generated process data to reduce the time and cost consuming reference measurement effort for multivariate calibration. To determine metabolite concentrations with accuracies between ±0.19 and ±0.96·gL−l, the presented utilisation needs primarily — besides online sensor measurements — single FTIR measurements for each of the components of interest. The ambiguities in alternating least squares solutions for concentration estimation are reduced by the insertion of analytical process knowledge primarily in the form of elementary carbon mass balances. Thus, in this way, the established idea of mass balance constraints in MCR combines with the consistency check of measured data by carbon balances, as commonly applied in bioprocess engineering. The constraints are calculated based on online process data and theoretical assumptions. This increased calculation effort is able to replace, to a large extent, the need for manually conducted quantitative chemical analysis, leads to good estimations of concentration profiles and a better process understanding.
Many borate crystals feature nonlinear optical properties that allow for efficient frequency conversion of common lasers down into the ultraviolet spectrum. Twinning may degrade crystal quality and affect nonlinear optical properties, in particular if crystals are composed of twin domains with opposing polarities. Here, we use measurements of optical activity to demonstrate the existence of inversion twins within single crystals of YAl3(BO3)4 (YAB) and K2Al2B2O7 (KABO). We determine the optical rotatory dispersion of YAB and KABO throughout the visible spectrum using a spectrophotometer with rotatable polarizers. Space-resolved measurements of the optical rotation can be related to the twin structure and give estimates on the extent of twinning. The reported dispersion relations for the rotatory power of YAB and KABO may be used to assess crystal quality and to select twin-free specimens.
Concerns over climate change, air pollution, and oil supply have stimulated the market for battery electric vehicles (BEVs). The environmental impacts of BEVs are typically evaluated through a standardized life-cycle assessment (LCA) methodology. Here, the LCA literature was surveyed with the objective to sketch the major trends and challenges in the impact assessment of BEVs. It was found that BEVs tend to be more energy efficient and less polluting than conventional cars. BEVs decrease exposure to air pollution as their impacts largely result from vehicle production and electricity generation outside of urban areas. The carbon footprint of BEVs, being highly sensitive to the carbon intensity of the electricity mix, may decrease in the nearby future through a shift to renewable energies and technology improvements in general. A minority of LCAs covers impact categories other than carbon footprint, revealing a mixed picture. Up to date little attention is paid so far in LCA to the efficiency advantage of BEVs in urban traffic, the gap between on-road and certified energy consumption, the local exposure to air pollutants and noise and the aging of emissions control technologies in conventional cars. Improvements of BEV components, directed charging, second-life reuse of vehicle batteries, as well as vehicle-to-home and vehicle-to-grid applications will significantly reduce the environmental impacts of BEVs in the future.
Background: On the way to a more sustainable society, transport needs to be urgently optimized regarding energy consumption and pollution control. While in earlier decades, Europe followed automobile technology leaps initiated in the USA, it has decoupled itself for 20 years by focusing research capacity towards the diesel powertrain. The resulting technology shift has led to some 45 million extra diesel cars in Europe. Its outcome in terms of health and environmental effects will be investigated below.
Results: Expected greenhouse gas savings initiated by the shift to diesel cars have been overestimated. Only about one tenth of overall energy efficiency improvements of passenger cars can be attributed to it. These minor savings are on the other hand overcompensated by a significant increase of supply chain CO2 emissions and extensive black carbon emissions of diesel cars without particulate filter. We conclude that the European diesel car boom did not cool down the atmosphere. Moreover, toxic NO x emissions of diesel cars have been underestimated up to 20-fold in officially announced data. The voluntary agreement signed in 1998 between the European Automobile industry and the European Commission envisaging to reduce CO2 emissions has been identified as elementary for the ensuing European diesel car boom. Four factors have been quantified in order to explain very different dieselization rates across Europe: impact of national car/supplier industry, ecological modernization, fuel tourism and corporatist political governance. By comparing the European diesel strategy to the Japanese petrol-hybrid avenue, it becomes clear that a different road would have both more effectively reduced CO2 emissions and pollutants.
Conclusion: Europe's car fleets have been persistently transformed from being petrol-driven to diesel-driven over the last 20 years. This paper investigates on how this came to be and why Europe took a distinct route as compared to other parts of the world. It also attempts to evaluate the outcome of stated goals of this transformation which was primarily a robust reduction in GHG emissions. We conclude that global warming has been negatively affected, and air pollution has become alarming in many European locations. More progressive development scenarios could have prevented these outcomes.
Optimal mental workload plays a key role in driving performance. Thus, driver-assisting systems that automatically adapt to a drivers current mental workload via brain–computer interfacing might greatly contribute to traffic safety. To design economic brain computer interfaces that do not compromise driver comfort, it is necessary to identify brain areas that are most sensitive to mental workload changes. In this study, we used functional near-infrared spectroscopy and subjective ratings to measure mental workload in two virtual driving environments with distinct demands. We found that demanding city environments induced both higher subjective workload ratings as well as higher bilateral middle frontal gyrus activation than less demanding country environments. A further analysis with higher spatial resolution revealed a center of activation in the right anterior dorsolateral prefrontal cortex. The area is highly involved in spatial working memory processing. Thus, a main component of drivers’ mental workload in complex surroundings might stem from the fact that large amounts of spatial information about the course of the road as well as other road users has to constantly be upheld, processed and updated. We propose that the right middle frontal gyrus might be a suitable region for the application of powerful small-area brain computer interfaces.
This article presents experience curves and cost-benefit analyses for electric and plug-in hybrid cars sold in Germany. We find that between 2010 and 2016, the prices and price differentials relative to conventional cars declined at learning rates of 23 ± 2% and 32 ± 2% for electric cars and 6 ± 1% and 37 ± 2% for plug-in hybrids. If trends persist, price beak-even with conventional cars may be reached after another 7 ± 1 million electric cars and 5 ± 1 million plug-in hybrids are produced. The user costs of electric and plug-in hybrid cars relative to their conventional counterparts are declining annually by 14% and 26%. Also the costs for mitigating CO2 and air pollutant emissions through the deployment of electrified cars tend to decline. However, at current levels, NOX and particle emissions are still mitigated at lower costs by state-of-the-art after-treatment systems than through the electrification of powertrains. Overall, the observation of robust technological learning suggests policy makers should focus their support on non-cost market barriers for the electrification of road transport, addressing specifically the availability of recharging infrastructure.
Purpose: The well-to-wheel (WTW) methodology is widely used for policy support in road transport. It can be seen as a simplified life cycle assessment (LCA) that focuses on the energy consumption and CO2 emissions only for the fuel being consumed, ignoring other stages of a vehicle’s life cycle. WTW results are therefore different from LCA results. In order to close this gap, the authors propose a hybrid WTW+LCA methodology useful to assess the greenhouse gas (GHG) profiles of road vehicles.
Methods: The proposed method (hybrid WTW+LCA) keeps the main hypotheses of the WTW methodology, but integrates them with LCA data restricted to the global warming potential (GWP) occurring during the manufacturing of the battery pack. WTW data are used for the GHG intensity of the EU electric mix, after a consistency check with the main life cycle impact (LCI) sources available in literature.
Results and discussion: A numerical example is provided, comparing GHG emissions due to the use of a battery electric vehicle (BEV) with emissions from an internal combustion engine vehicle. This comparison is done both according to the WTW approach (namely the JEC WTW version 4) and the proposed hybrid WTW+LCA method. The GHG savings due to the use of BEVs calculated with the WTW-4 range between 44 and 56 %, while according to the hybrid method the savings are lower (31–46 %). This difference is due to the GWP which arises as a result of the manufacturing of the battery pack for the electric vehicles.
Conclusions: The WTW methodology used in policy support to quantify energy content and GHG emissions of fuels and powertrains can produce results closer to the LCA methodology by adopting a hybrid WTW+LCA approach. While evaluating GHG savings due to the use of BEVs, it is important that this method considers the GWP due to the manufacturing of the battery pack.
A local non-restrictive ramp metering strategy PRO is introduced. It is based on the stochasticity of capacity. The ramp metering algorithm shows innovative features:
• upstream time shifted measurements for anticipation
• measurements are actuated every second
• up to three vehicles per green are allowed
Details of the theory of this strategy are described in the first part. At freeway B27 three ramp meters with the PRO algorithm were installed. In the second part, based on extensive detailed traffic and accident data the effects on traffic flow and safety are described. The impact is positive regarding vehicle speed, queue duration and length as well as capacity and traffic safety. The improvements of speeds, travel times and capacities are statistically significant. The ramp metering systems are highly cost effective.
