Background and Goals
The two megatrends of demographic change and climate change interact by risks in the context of climate change resulting not only from the physical changes in climate, but solely from their interaction with social development processes. Both trends are characterized by their longevity and growing importance as well as their low predictability, especially at smaller scale levels. Dealing with the demographic change in cities is based on projections of population and household which assume a number of different assumptions, depending on origin and destination horizon of the forecast. However no known case take into account the medium and long-term consequences of climate change. In addition, the numerous publications on climate impacts and climate adaptation show that there is so far neither a single concept nor a single conceptual canon for the vulnerability assessment in spatial planning.
The research project presented here provides valuable insights into how the sensitivity of different urban structure types to climate change can be improved and how this knowledge can be incorporated into spatial planning in the context of planning. For this purpose the BMVBS climate change region types and the demographic types of the Bertelsmann Foundation are used.
The focus of the project is to analyze the influence of demographic change (population aging, population decline or increase in cash, heterogeneity of the population) on the sensitivity of cities to the impacts of climate change.
- What impact do specific urban climatic or urban structural factors have on the effects of climate change?
- How does demographic change change the meaning of sensitivity compared to the importance of the climate signal over time and to different types of cities?
- What are the challenges for adaptive planning for different types of cities?
Content time
toResearch area/region
- Germany
- Nationwide
- Nationwide
Steps in the process of adaptation to climate change
Step 1: Understand and describe climate change
Development of an integrated methodology for estimating the effects of climate change for three points in time: present, near future and distant future. The basis was provided by climate signals, sensitivities and effects.
Climatic space types (KRTs) show spatial priorities of current and future climate impacts (2030, 2100), which are similar in their combination of climatic features - strong winds, heavy rainfall, hot days, tropical nights, frost days, average temperatures, dry days, precipitation.
By intersecting types of demographics and types of climatic space, it was possible to show spatial statements about the causal relationships in theory.
- Heat waves
- Altered rainfall patterns
- Higher average temperatures
- Extreme precipitation (incl. hail, snow)
- Dry periods
Strong wind, frosty days, tropical nights, hot days
- Presence
- Near Futur
- Distant Future
Step 4: Plan and implement measures
Procedures, tools, methods for planning resilient cities
- Procedure: sequential realization of plan contents, parametric governance
- Formal instruments: urban development contract, urban renewal measures, temporary construction law, multifunctional land use, simple development plan, heritable building right
- Informal instruments: integrated urban development concepts, land cycle economy
- Methods: Backcasting, indicator-based monitoring
New perspectives for the planning of resilient cities
- Time before layout for experiments & reinterpretation
- Adaptive planning checklist: more flexible definitions, construction requirements, instructions, recommendations
- Involve planners even after planning approval
- Changes are possible in FNP and B-Plan
- instruments
- leasehold
- Multifunctional land use
- Integrated urban development concepts
measures
- Roof / facade greening
- High albedo
- Greening and shading
- Public transport stops with weather protection
- Public drinking water sources
- Adaptation of different building typologies with sufficient retroreflectivity, evaporation and infiltration possibilities, greening, ventilation options, shading
Participants
Support by the German Research Foundation (DFG)
Department of spatial planning and planning theory, Technical University Dortmund
Institute of Spatial Planning (IRPUD), Technical University Dortmund
Institute of Spatial Planning (IRPUD)
Technical University Dortmund
August-Schmidt-Straße 10
44227 Dortmund