This Deliverable D2.1 forms part of the context‐setting for the REGREEN project, and describes the main drivers and pressures associated with urbanization which are the focus of the Urban Living Labs (ULLs) within the project. The pressures are primarily environmental, but shaped by social and economic factors. The report illustrates how social factors interact with green, blue and grey infrastructure to shape the opportunities for implementing NBS to address these challenges. Contributors to this report come from WP2 (challenges), WP3 (mapping and modelling) and all six ULLs: Paris, Aarhus, Velika Gorica, Shanghai, Beijing and Ningbo. Each ULL ranks and describes the main pressures facing them. Air pollution, noise and heat are the top three pressures in Beijing and Velika Gorica. In Aarhus and Paris, the top three are biodiversity loss, water quality and flooding. In the other two Chinese ULLs, Ningbo and Shanghai, the top three issues are air pollution, water quality and flooding. These pressures are explored in more detail, including the health and societal impacts they cause. Urban sprawl is separately addressed as a pressure, illustrated by a historical analysis of the rate of change in urban extent in all six ULLs since 1985. The expansion of urban area in the Chinese ULLs is substantially greater than any of the European ULLs. Social and economic factors, which influence vulnerability and exposure to pressures, are also discussed. The literature suggests that age is the main risk factor for negative health impacts from high‐temperatures, while deprivation is a risk factor for PM2.5 associated health impacts. The report discusses the important role of spatial and temporal variability in pressures and in the potential of NBS to address these pressures. This highlights the importance of capturing spatial and temporal variation in data representing the pressures, but also that it is critical to have appropriate contextual data, particularly those data relating to people (e.g. sociodemographic and socioeconomic data) in order to provide useful spatially and temporally explicit representations of the challenges that are produced in urban environments.