Materials in Germany's building stock: calculation model data and uncertainties

Around the world, building stocks are the dominant consumers of resources within national economies. Correspondingly, there is high demand for improved knowledge of material stocks and flows in the built environment. Material... [ view full abstract ]

Around the world, building stocks are the dominant consumers of resources within national economies. Correspondingly, there is high demand for improved knowledge of material stocks and flows in the built environment. Material flow analysis (MFA) is well suited to meet this demand. Numerous studies have been conducted on this topic over years, whereby emphasis has been placed on coefficient-based bottom-up approaches. However, the literature reveals two major weaknesses that limit the applicability and transferability of such approaches as well as the quality of results: Frequently the analysis of material stocks and flows is difficult to reproduce and methods are insufficiently documented. This hinders comparative studies and the discussion of transferability of results at an international level. A second limitation is in the treatment of uncertainties. These are frequently overlooked, which of course undermines any attempt to estimate the reliability of results. Based on two studies (Ortlepp, Gruhler & Schiller 2015, 2016), an approach for calculating material stocks and flows for domestic and non-domestic buildings will be presented. We will take a close look at the creation of highly specific material composition indicators (MCI) that form the basis for model calculations und will present approaches to examine parameter-related and model-related uncertainties.

In Germany the total material mass of non-domestic buildings is approximately 6.8 billion tonnes, accounting for 44% of the entire building stock. Further main results are age-based MCIs for domestic buildings, the total material mass as well as quantitative information on parameter-related and model-related uncertainties. Non-domestic buildings’ MCIs are differentiated by 7 usage types according to the German official building statistic. The results such as MCI are available in the IOER open access database (www.bdat.ioer.eu).

Bottom-up MFA is a suitable method to quantify stocks and flows of materials in complex systems. Such approaches offer high flexibility in model design and in the differentiation of results. At the same time MFA has the following drawbacks: There is a lack of statistical data from which representative input parameters can be generated using mathematical techniques. The creation of an empirical basis for the provision of input parameters is time-consuming and complex. Usually it is necessary to resort to case studies. In this way, results are inherently non-representative due to small sample sizes. Expert knowledge is essential in order to generalize empirical base data. This process is associated with uncertainty. Therefore, one primary requirement of MFA is the transparent and comprehensible documentation of methods, base data and results to enable (1) comparative investigations, (2) the possibility of model transferability across national borders, and (3) an estimation of the validity of applied parameters and results. This serves both to improve the empirical basis as well as the validation of own investigations.

Ortlepp, R.; Gruhler, K.; Schiller, G. (2016): Materials in Germany’s domestic building stock: calculation model and uncertainties In: Building Research & Information (Online First). http://dx.doi.org/10.1080/0961... Ortlepp, R.; Gruhler, K.; Schiller, G. (2016): Material stocks in Germany’s non-domestic buildings: a new quantification method In: Building Research & Information 44 (2016) 8, pp. 840-862. http://dx.doi.org/10.1080/09613218.2016.1112096.