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A. Mahdavi, K. Kiesel, M. Vuckovic:
"Empirical and computational assessment of the urban heat island phenomenon and related mitigation measures";
Talk: NSB2014 - 10th Nordic Symposium on Building Physics, Lund, Schweden; 2014-06-15 - 2014-06-19; in: "NSB2014 - 10th Nordic Symposium on Building Physics", J. Arfvidsson, L.E. Harderup, A. Kumlin, B. Rosencrantz (ed.); (2014), ISBN: 978-91-88722-51-5; 566 - 573.

A central strand of research work in the realm of urban physics aims at a better understanding of the
variance in microclimatic conditions due to factors such as building agglomeration density,
anthropogenic heat production, traffic intensity, presence and extent of green areas and bodies of
water. This research has been motivated in part by phenomena associated with climate change and
urban heat islands (UHI) and their implications for the urban microclimate. Note that the
characteristics and evolution of the urban microclimate is not only relevant to people's experience of
outdoor thermal conditions in the cities. It could be argued that the solid understanding of the
temporal and spatial variance of urban microclimate represents a prerequisite for the reliable
assessment of the thermal performance of buildings (energy requirements, indoor thermal conditions).
In this context, the present paper entails a three-fold contribution. First, the existence and extent of the
UHI phenomena are documented for a number of Central-European cities. Second, a number of
variables of the urban environment are identified that are hypothesized to influence UHI and the
urban microclimate variance. These variables, which pertain to both geometric (morphological) and
semantic (material-related) urban features are captured within a formal and systematic framework.
Third, to support the process of design and evaluation of UHI mitigation measures, the potential of
both numerical (simulation-based) applications and empirically-based urban microclimate models are
explored.

none - see english version

Urban climate Urban Heat Island, Mitigation Measure, Modeling, Evaluation