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For a successful transformation towards a sustainable bioeconomy, cooperative knowledge creation leading to innovations through research at the company and academic level are important. Urban regions are the centre of economic and research activities. The example of the region of Stuttgart, which aims to complement its mature industrial structure with new opportunities related to the knowledge-based bioeconomy, is an interesting case for the application of social network analysis to shed light on the dynamics of innovation networks to support the transformation of urban regions. As with smaller spatial levels of observation connectivity in network decreases, we find a scale-free network structure for the supra-regional network and a star-like network structure for the regional network, with two universities and one transfer-oriented research institutes at the core. While research collaborations beyond regional borders and across different industries foster knowledge co-creation, the central actors can be recognized as gatekeepers who dominantly influence knowledge flows. To potentially strengthen the resilience of the network, policy and industry associations serving as network facilitators can foster collaboration between periphery actors. The case of the Stuttgart region impressively illustrates the opportunities of the knowledge-based bioeconomy for urban regions and the complementary role traditional manufacturing sectors can take in the transformation towards higher degrees of sustainability. [ABSTRACT FROM AUTHOR]

Wind speed is reduced above urban areas due to their high aerodynamic roughness. This not only holds for above the urban canopy. The local vertical wind profile is modified. Aerodynamic roughness (both roughness length and displacement height) therefore is relevant for many fields within human biometeorology, e.g. for the identification of ventilation paths, the concentration and dispersion of air pollutants at street level or to simulate wind speed and direction in urban environments and everything depending on them. Roughness, thus, also shows strong influence on human thermal comfort. Currently, roughness parameters are mostly estimated using classifications. However, such classifications only provide limited assessment of roughness in urban areas. In order to calculate spatially resolved roughness on the micro-scale, three different approaches were implemented in the SkyHelios model. For all of them, the urban area is divided into reference areas for each of the obstacles using a voronoi diagram. The three approaches are based on building and [+one of them also on] vegetation (trees and forests) data. They were compared for the city of Stuttgart, Germany. Results show that the approach after Bottema and Mestayer (J Wind Eng Ind Aerodyn 74-76:163-173 1998) on the spatial basis of a voronoi diagram provides the most plausible results. [ABSTRACT FROM AUTHOR]