Towards modelling of construction, renovation and demolition activities: Norway's dwelling stock, 1900–2100

Sartori, Igor; Bergsdal, Håvard; Müller, Daniel B.; Brattebø, Helge

doi:10.1080/09613210802184312

Cited by 75 publications

(42 citation statements)

References 15 publications

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“…In Sartori et al (2008), the input parameters are the same as in Bergsdal et al (2007), except that a smooth regression curve is used for population data input instead of actual statistics. The model output is compared with census data from Statistics Norway (2001), showing that the modelled UFA is 9.6%, 5.4% and 0.4% 3 higher for 1980, 1990 and 2001, respectively.…”

Section: Development In Useful Floor Area and Building Materials Concementioning

confidence: 99%

“…They investigated the effects of variations in the underlying driving factors on UFA and material stocks and flows, covering a long time span from 1900 to 2100, calibrating the model with empirical data before 2004 and performing scenario simulations from 2005 onwards. Sartori et al (2008) further developed the model used in Bergsdal et al (2007) in order to cover renovation activity in a better way. Scenarios for future development are compared to analyse the model's sensitivity to uncertainty in the input parameters and results are compared with available statistical data.…”

Section: Stock-£ow Modelsmentioning

confidence: 99%

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Historical energy analysis of the Norwegian dwelling stock

Sandberg

Bergsdal

Brattebø

2011

Building Research & Information

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and helge.brattebo@ntnu.noThe building sector is a big consumer of energy and is responsible for a considerable share of the greenhouse gas emissions within most developed countries. Based on the development in underlying drivers and using system analysis methods, the historical development in energy flows in the Norwegian residential building stock, the associated costs and greenhouse gas emissions are estimated. The results show that although a 39% decrease occurred in energy consumption per square metre in the use phase, the total energy consumption increased due to increased stock size. Further, the total energy consumption was substantially dominated by the use phase. The energy-related costs increase even more than energy consumption due to increased energy prices, but the greenhouse gas emissions decrease due to changes in the energy mix. The per-capita results follow the same trends as the aggregated results, whereas there have been larger improvements in the system on a per-square-metre basis. Based on underlying drivers, the model ensures inclusion of development trends that are not easily explained by the direct factors energy efficiency, energy mix and energy prices.Keywords: building stock, carbon footprint, cost analysis, dwelling stock, dynamic material flow analysis, economic footprint, energy consumption, energy efficiency, greenhouse gas emissions Le secteur du bâ timent est un gros consommateur d'énergie et est responsable d'une part considérable des émissions de gaz à effet de serre dans la plupart des pays développés. En se basant sur l'évolution des facteurs sous-jacents et en utilisant des méthodes d'analyse des systèmes, sont estimés l'évolution historique des flux d'énergie dans le parc bâ ti résidentiel norvégien, les coû ts qui s'y rapportent et les émissions de gaz à effet de serre. Les résultats montrent que, bien qu'une diminution de 39% soit intervenue dans la consommation d'énergie par mètre carré dans la phase d'utilisation, la consommation totale d'énergie a augmenté en raison de la taille accrue du parc. En outre, la consommation totale d'énergie a été fortement dominée par la phase d'utilisation. Les coû ts liés à l'énergie augmentent encore plus que la consommation d'énergie du fait de l'augmentation des prix de l'énergie, mais les émissions de gaz à effet de serre diminuent en raison des changements intervenus dans le mix énergétique. Les résultats par personne suivent les mêmes tendances que les résultats agrégés, alors que des améliorations plus importantes se sont produites dans le système sur la base du mètre carré. En se basant sur les facteurs sous-jacents, le modèle assure l'inclusion de tendances évolutives qui ne s'expliquent pas facilement par les facteurs directs d'efficacité énergétique, de mix énergétique et de prix de l'énergie.Mots clés: parc bâ ti, empreinte carbone, analyse des coû ts, parc de logements, analyse dynamique des flux de matériaux, empreinte économique, consommation d'énergie, efficacité énergétique, émissions de gaz à effet de serre

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Section: Development In Useful Floor Area and Building Materials Concementioning

confidence: 99%

Section: Stock-£ow Modelsmentioning

confidence: 99%

Historical energy analysis of the Norwegian dwelling stock

Sandberg

Bergsdal

Brattebø

2011

Building Research & Information

Self Cite

View full text Add to dashboard Cite

show abstract

“…To name only a few examples from the literature, the first method is probably ubiquitous (where available); the second has been used by Gleeson (1985Gleeson ( , 1986, Johnstone (2001aJohnstone ( , 2001b and by Meinen et al (1998); random sampling was used in Bradley and Kohler (2007) and Kohler et al (1999); and the physical model approach in Bergsdal et al (2007) and Sartori et al (2008).…”

Section: Introductionmentioning

confidence: 98%

An ultrametric interpretation of building related event data

Bradley

2010

Construction Management and Economics

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The long-term behaviour of the built environment is relevant to practising architects and engineers as well as to investors and policy makers. In contrast to this, the size, structure and dynamics of that important capital of society are not well established. As a first step towards assessing the dynamics of new constructions, refurbishments, demolitions and other building related event variables in urban building stocks in Southwest Germany, a first random sample of event data is examined using the more efficient ultrametric hierarchical classification in order to compare their dynamics. To this end, different ways of binary encodings of the multivariate data are carried out, and their ultrametric classification results compared. It turns out that municipalities of comparable sizes show similar behaviour in contrast to those of differing sizes, which corresponds to previous findings. Consequently, ultrametric methods can be applied to the study of building stock dynamics by revealing inherent hierarchical structure in data.Building stock dynamics, hierarchical classification, ultrametric methods,

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“…The kgCO 2 unit was used for CO 2 emissions values related to the different stages. As the general application widely accepted related to the building lifetime is 30-50 years (Sartori, I., Bergsdal, H., Müller, D.B., Brattebø, H., 2008). The building lifetime stated by the Official Journal of the European Union (2012) is taken into account in this study, and the building lifetime is accepted as 30 years.…”

Section: Goal and Scope Definition For Lce And Lcco 2 Analysesmentioning

confidence: 99%

Life cycle assessment of energy retrofit strategies for an existing residential building in Turkey

Mangan¹,

Oral²

2016

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Energy consumption in residential buildings contributes significantly to negative environmental impacts such as climate change and ozone depletion, and the implication for carbon dioxide emissions reductions in buildings during the construction phase as the embodied carbon and the operation phase in the form of operational carbon are widely acknowledged. Investment on creating a sustainable built environment especially through energy retrofit strategies for buildings has been progressively increasing over the last decade. To identify optimum energy retrofit strategies for reducing both energy consumption and CO 2 emissions, this paper presents a simplified life cycle model and implements this to a case study focused on different climate regions of Turkey. The objective of this study is to develop effective strategies on the improvement of building energy performance for different climate regions, which is important for optimum use in the sense of country resources and decision makers. Also the energy and environmental performances of the residential buildings regarding these strategies are assessed on the basis of a comparative method in the framework of life cycle. In this study based on life cycle energy and environmental performance, the alternatives related to energy retrofit strategies were evaluated in order to improve the energy performance of the existing residential buildings. In this context, the effect of each measure on life cycle energy consumption and CO 2 emissions was determined by using the "Life Cycle Energy (LCE)" and "Life Cycle CO 2 (LCCO 2 )" analyses developed based on the life cycle assessment (LCA) method.

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Towards modelling of construction, renovation and demolition activities: Norway's dwelling stock, 1900–2100

Cited by 75 publications

References 15 publications

Historical energy analysis of the Norwegian dwelling stock

Historical energy analysis of the Norwegian dwelling stock

An ultrametric interpretation of building related event data

Life cycle assessment of energy retrofit strategies for an existing residential building in Turkey

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