A Comparative Review of Existing Data and Methodologies for Calculating Embodied Energy and Carbon of Buildings

In the Climate Change Act of 2008 the UK Government pledged to reduce carbon emissions by 80% by 2050. As one step towards this, regulations are being introduced requiring all new buildings to be ‘zero carbon’ by 2019. These are defined as buildings which emit net zero carbon during their operational lifetime. However, in order to meet the 80% target it is necessary to reduce the carbon emitted during the whole life-cycle of buildings, including that emitted during the processes of construction. These elements make up the ‘embodied carbon’ of the building. While there are no regulations yet in place to restrict embodied carbon, a number of different approaches have been made. There are several existing databases of embodied carbon and embodied energy. Most provide data for the material extraction and manufacturing only, the ‘cradle to factory gate’ phase. In addition to the databases, various software tools have been developed to calculate embodied energy and carbon of individual buildings. A third source of data comes from the research literature, in which individual life cycle analyses of buildings are reported. This paper provides a comprehensive review, comparing and assessing data sources, boundaries and methodologies. The paper concludes that the wide variations in these aspects produce incomparable results. It highlights the areas where existing data is reliable, and where new data and more precise methods are needed. This comprehensive review will guide the future development of a consistent and transparent database and software tool to calculate the embodied energy and carbon of buildings.

Improving data quality in DSM modelling: A structural comparison approach

The Dependency Structure Matrix (DSM) has proved to be a useful tool for system structure elicitation and analysis. However, as with any modelling approach, the insights gained from analysis are limited by the quality and correctness of input information. This paper explores how the quality of data in a DSM can be enhanced by elicitation methods which include comparison of information acquired from different perspectives and levels of abstraction. The approach is based on comparison of dependencies according to their structural importance. It is illustrated through two case studies: creation of a DSM showing the spatial connections between elements in a product, and a DSM capturing information flows in an organisation. We conclude that considering structural criteria can lead to improved data quality in DSM models, although further research is required to fully explore the benefits and limitations of our proposed approach.

Automated Detection of Concrete Columns from Visual Data

After earthquakes, licensed inspectors use the established codes to assess the impact of damage on structural elements. It always takes them days to weeks. However, emergency responders (e.g. firefighters) must act within hours of a disaster event to enter damaged structures to save lives, and therefore cannot wait till an official assessment completes. This is a risk that firefighters have to take. Although Search and Rescue Organizations offer training seminars to familiarize firefighters with structural damage assessment, its effectiveness is hard to guarantee when firefighters perform life rescue and damage assessment operations together. Also, the training is not available to every firefighter. The authors therefore proposed a novel framework that can provide firefighters with a quick but crude assessment of damaged buildings through evaluating the visible damage on their critical structural elements (i.e. concrete columns in the study). This paper presents the first step of the framework. It aims to automate the detection of concrete columns from visual data. To achieve this, the typical shape of columns (long vertical lines) is recognized using edge detection and the Hough transform. The bounding rectangle for each pair of long vertical lines is then formed. When the resulting rectangle resembles a column and the material contained in the region of two long vertical lines is recognized as concrete, the region is marked as a concrete column surface. Real video/image data are used to test the method. The preliminary results indicate that concrete columns can be detected when they are not distant and have at least one surface visible.

A Comparative Review of existing data and methodologies for calculating embodied energy and carbon of buildings

In the Climate Change Act of 2008 the UK Government pledged to reduce carbon emissions by 80% by 2050. As one step towards this, regulations are being introduced requiring all new buildings to be ‘zero carbon’ by 2019. These are defined as buildingswhichemitnetzerocarbonduringtheiroperationallifetime.However,inordertomeetthe80%targetitisnecessary to reduce the carbon emitted during the whole life-cycle of buildings, including that emitted during the processes of construction. These elements make up the ‘embodied carbon’ of the building. While there are no regulations yet in place to restrictembodiedcarbon,anumberofdifferentapproacheshavebeenmade.Thereareseveralexistingdatabasesofembodied carbonandembodiedenergy.Mostprovidedataforthematerialextractionandmanufacturingonly,the‘cradletofactorygate’ phase. In addition to the databases, various software tools have been developed to calculate embodied energy and carbon of individual buildings. A third source of data comes from the research literature, in which individual life cycle analyses of buildings are reported. This paper provides a comprehensive review, comparing and assessing data sources, boundaries and methodologies. The paper concludes that the wide variations in these aspects produce incomparable results. It highlights the areas where existing data is reliable, and where new data and more precise methods are needed. This comprehensive review will guide the future development of a consistent and transparent database and software tool to calculate the embodied energy and carbon of buildings.