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We have developed a method that enables better taking into account of need of space of actions of moving objects in a building when Building Information Modeling (BIM) is used. The 3D spatial objects for real space requirements of actions created with our method can be used with various design tools as such in dimensioning or to generate video game colliders defining the need of space. Together with the gamified model of the structure from BIM they enable dimensioning in designs and simulations. We can dimension spatial objects for example related to safety. There are a lot of needs and applications for our methods. It is possible to design buildings and other structures that fit their purpose well.

The science of statistics contributes to the development and application of tools for the design, analysis, and interpretation of empirical medical studies [...]

Medium and heavy-duty battery electric trucks (BETs) may play a key role in mitigating greenhouse gas (GHG) emissions from road freight transport. However, technological challenges such as limited range and cargo carrying capacity as well as the required charging time need to be efficiently addressed before the large-scale adoption of BETs. In this study, we apply a geospatial data analysis approach by using a battery electric vehicle potential (BEVPO) model with the datasets of road freight transport surveys for analyzing the potential of large-scale BET adoption in Finland and Switzerland for trucks with gross vehicle weight (GVW) of over 3.5 t. Our results show that trucks with payload capacities up to 30 t have the most potential for electrification by relying on the currently available battery and plug-in charging technology, with 93% (55% tkm) and 89% (84% tkm) trip coverage in Finland and Switzerland, respectively. Electric road systems (ERSs) would be essential for covering 51% trips (41% tkm) of heavy-duty trucks heavier than 30 t in Finland. Furthermore, range-extender technology could improve the trip electrification potential by 3–10 percentage points (4–12 percentage points of tkm).

The building sector contributes up to 30% of global annual greenhouse gas emissions and consumes up to 40% of all energy. Failure to encourage energy-efficiency and low-carbon in new builds or retrofitting will lock countries into the disadvantages of poor performing buildings for decades. The journey towards low-carbon and energy efficient buildings starts with good design, commissioning and measuring. The share of energy costs can be up to 50% of all maintenance costs [7] in Finland. In the studied buildings the average costs were 39% for daycare centres and 45% for schools. Since the share of energy costs is remarkable in maintenance, it is important to find out the most concrete indicators to measure energy efficiency in practice. This study explores ways in which building usage and occupancy influences the energy cost in Finnish daycare centres and school buildings. This study shows that energy costs vary a lot between different energy efficiency indicators, i.e. there is great variation in energy costs regardless of the building age and when child or student density varies. Results indicated that actual use of space is profiled in the operational phase where the energy costs variation is remarkable.

Abstract The aim of this review is to discuss how quantitative modelling of energy scenarios for sustainable energy transition pathways can be made more realistic by taking into account insights from the socio-technical and related literatures. The proposition is that an enriched modelling approach would focus not just on technology development and deployment, but also on feedback loops, learning processes, policy and governance, behavioural changes, the interlinkages between the energy sector and other economic sectors, and infrastructure development. The review discusses a range of socio-technical concepts with a view to how they can enrich the understanding and modelling of highly complex dynamic systems such as flexible energy systems with high shares of variable renewable energy. In this context, application of system dynamics modelling (SDM) for the analysis of energy transitions is also introduced by describing the differences between SDM and a traditional modelling approach that uses econometric and linear programming methods. A conceptual framework for this type of modelling is provided by using causal loop diagrams. The diagrams illustrate the endogenous approach of SDM – understanding and modelling the structure of a system, which is responsible for its dynamic behaviour. SDM can also capture the co-evolution of economic, policy, technology, and behavioural factors over sufficiently long time periods, which is necessary for the analysis of transition pathway dynamics. In this regard, the review summarises how socio-technical concepts can be approached in SDM and why they are relevant for the analysis of flexibility in energy systems. From a computational point of view, it could be beneficial to combine SDM with technologically detailed energy system optimization models and that could be a way forward for achieving more realistic, non-linear quantitative modelling of sustainable energy transitions.

The European Union is currently in the process of transformation toward a circular economy model in which different areas of activity should be integrated for more efficient management of raw materials and waste. The wastewater sector has a great potential in this regard and therefore is an important element of the transformation process to the circular economy model. The targets of the circular economy policy framework such as resource recovery are tightly connected with the wastewater treatment processes and sewage sludge management. With this in view, the present study aims to review existing indicators on resource recovery that can enable efficient monitoring of the sustainable and circular solutions implemented in the wastewater sector. Within the reviewed indicators, most of them were focused on technological aspects of resource recovery processes such as nutrient removal efficiency, sewage sludge processing methods and environmental aspects as the pollutant share in the sewage sludge or its ashes. Moreover, other wide-scope indicators such as the wastewater service coverage or the production of bio-based fertilizers and hydrochar within the wastewater sector were analyzed. The results were used for the development of recommendations for improving the resources recovery monitoring framework in the wastewater sector and a proposal of a circularity indicator for a wastewater treatment plant highlighting new challenges for further researches and wastewater professionals.

The outbreak of SARS-COV-2 disease 2019 (COVID-19) abruptly changed the patterns in electricity consumption, challenging the system operations of forecasting and balancing supply and demand. This is due to the mitigation measures that include lockdown and Work from Home (WFH), which decreased the aggregated demand and remarkably altered its profile. Here, we characterise these changes with various quantitative markers and compare it with pre-COVID-19 business-as-usual data using Great Britain (GB) as a case study. The ripple effects on the generation portfolio, system frequency, forecasting accuracy and imbalance pricing are also analysed. An energy data extraction and pre-processing pipeline that can be used in a variety of similar studies is also presented. Analysis of the GB demand data during the March 2020 lockdown indicates that a shift to WFH will result to a net benefit for flexible stakeholders, such as consumer on variable tariffs. Furthermore, the analysis illustrates a need for faster and more frequent balancing actions, as a result of the increased share of renewable energy in the generation mix. This new equilibrium of energy demand and supply will require a redesign of the existing balancing mechanisms as well as the longer-term power system planning strategies.