Compact cities have been attributed to lower per capita energy use. However, the complexity of relationships between the elements that constitute energy consumption in the urban system is poorly understood. Little or no research exist on the relation between energy costs of building taller, and transportation and infrastructure energy benefits of building denser. This study provides a theoretical assessment of how energy use is related to urban density in a densely populated area, to aid the development of sustainable cities and land-use planning. The paper builds a holistic parametric model to estimate the total urban energy use for space heating, embodied building energy, transportation energy, and road infrastructure energy, and how these relate to urban density. It does so by varying building height and other urban characteristics related to density, with the aim of identifying the most influential parameters with regard to energy consumption. The possibility of an optimal building height and urban density is also investigated. A much denser and taller city structure than what is normal in cities today appears to be optimal for low urban energy use. The most influential urban density indicators are found to be the dwelling service level (m2/cap) and the building design lifetime. Transportation energy becomes increasingly important with a rise in population. Results indicate that depending on population and building lifetime there exists an optimal building height in the range of 7-27 stories. Climate is found to significantly influence the energy results. These preliminary findings are indicative of general trends, but further research and development of the model are needed to reduce uncertainties
Low‐energy building standards shift environmental impacts from the operational to the embodied emissions, making material efficiency (ME) important for climate mitigation. To help quantify the mitigation potential of ME strategies, we developed a model that simulates the temporal material flows and greenhouse gas embodied emissions (GEEs) of the material use in the construction and renovation activities of a neighborhood by combining life‐cycle assessment with dynamic material‐flow analysis methods. We applied our model on a “zero emission neighborhood” project, under development from 2019 to 2080 and found an average material use of 1,049 kg/m2, an in‐use material stock of 43 metric tons/cap, and GEEs of 294 kgCO2e/m2. Although 52% of the total GEEs are caused by material use during initial construction, the remaining 48% are due to material replacements in a larger timeframe of 45 years. Hence, it is urgent to act now and design for ME over the whole service life of buildings. GEEs occurring far into the future will, however, have a reduced intensity because of future technology improvements, which we found to have a mitigation potential of 20%. A combination of ME strategies at different points in time will best mitigate overall GEEs. In the planning phase, encouraging thresholds on floor area per inhabitant can be set, materials with low GEEs must be chosen, and the buildings should be designed for ME and in a way that allows for re‐use of elements. Over time, good maintenance of buildings will postpone the renovation needs and extend the building lifetime.
There is a growing body of research on the embodied emissions of individual buildings, but the results and methods remain mostly inaccessible and incomparable due to insufficient reported information, and differences in system boundaries, methods, and data used. This inhibits further utilization of the results in statistical applications and makes interpretation and validation of results difficult. The database tool presented in this paper attempts to mitigate these challenges by systematizing and storing all relevant information for these studies in a compatible format. The tool enables comparison of results across system boundaries, improves the transparency and reproducibility of the assessments, and makes utilization of the results in statistical applications possible. Statistical applications include embodied emission benchmarking, identifying emission drivers, and quantifying relationships between variables. Other applications of the tool include the assessment of embodied emissions of buildings and neighborhoods. This paper presents the tool and exemplifies its use with preliminary results based on a dataset of 11 buildings. Work is ongoing to expand the dataset, which will provide more comprehensive results.
1 August 2019 in IOP Conference Series: Earth and Environmental Science
This paper addresses the role of virtual reality in addressing the specific challenge of the increasing complexity and decreasing usability when dealing with the level of detail required to model a zero emission neighbourhood (ZEN).[1] In such neighbourhoods, there is a need to handle both ‘top down’ neighbourhood level data with ‘bottom up’ building and material level data. This can quickly become overwhelming particularly when dealing with non expert users such as planners, architects, researchers and citizens who play a key part in the design process of future ZENs. Visualisation is an invaluable means to communicate complex data in an interactive way that makes it easier for diverse stakeholders to engage in decision making early and throughout the design process. The main purpose of this work has been to make ZEN key performance indicators (KPIs) more easily comprehensible to a diverse set of stakeholders who need to be involved in the early design phase. The paper investigates how existing extended reality (XR) technologies, such as virtual reality, can be integrated with an existing dynamic LCA method in order to provide visualise feedback on KPIs in early phase design of sustainable neighbourhoods. This existing method provides a dynamic link between the REVIT Bim and the ZEB Tool using a Dynamo plugin.[2] The results presented in this paper demonstrate how virtual reality can help to improve stakeholder participation in the early design phase and more easily integrate science-based knowledge on GHG emissions and other KPIs into the further development of the user-centered architectural and urban ZEN toolbox for the design and planning, operation and monitoring of ZENs. [3]