Climate Exposure Analysis: Identifying Vulnerable Places and Groups

In brief. An exposure analysis shows where and whom climate impacts hit hardest in your municipality. It links the question "where is the burden high?" with "who cannot protect themselves well?", for example older people, small children or the sick in densely built, green-poor neighbourhoods. The result directs measures to where they prevent the most damage. Honestly: the analysis names priorities, it does not make a value judgement for you.

Why this matters for your municipality. Resources are scarce, and not every neighbourhood can come first. An exposure analysis gives you an objective criterion for the order, instead of "whoever shouts loudest". This is politically relieving: you can justify why a particular district takes priority. At the same time, the exposure of vulnerable groups is a central reference point in funding programmes and in the climate adaptation act.

What does "exposure" mean technically?

Technically, vulnerability is made up of three building blocks. Exposure: how strongly is a place subject to the climate impact (many hot days, location in a depression)? Sensitivity: how sensitively do the people or uses located there react (share of very elderly people, daycare centre, care home)? Adaptive capacity: how well can they protect themselves (nearby green space, cool refuges, mobility)? Only the interplay produces a realistic picture. A hot place without people is less urgent than a slightly cooler one with a care home.

What data makes exposure visible?

You combine spatial and social data. Spatial: degree of sealing, green space provision, building density, location of cold air corridors, flood-prone depressions. Social: age structure from the residents' register (aggregated and compliant with data protection), locations of sensitive facilities such as schools, daycare centres, clinics, retirement and care homes. You overlay these layers. Where high exposure meets high sensitivity, that is where your hotspots lie. The Umweltbundesamt offers methodological guidance for this that can be broken down to the municipal level.

How do you use the result in planning?

The exposure map is a prioritisation tool. It shows where shading, desealing, drinking fountains or cool places to stay bring the greatest benefit. Link it to upcoming construction and renovation projects: where work is happening anyway and exposure is high, the most cost-effective lever arises. For heat protection of vulnerable groups, the analysis also provides target locations for outreach services and information chains on hot days.

The honest limit. Exposure is partly measurable, partly a matter of judgement: how strongly do you weight age against pre-existing conditions, social situation or language barriers? Such weightings are political and should be disclosed. Data gaps also remain: not every sensitivity is statistically recorded. The analysis makes what exists transparent, but does not replace conversations with local social and health actors.

When KomAdapt pays off. The risk and exposure analysis module brings the spatial and social layers together and makes the weightings traceable, so prioritisation remains verifiable rather than a matter of feeling. This particularly saves effort where social data and climate data have so far sat in separate departments.

_What is the difference between a risk assessment and an exposure analysis?_ The risk assessment looks at the overall risk from climate impact, probability and extent of damage. The exposure analysis focuses on the vulnerability of places and people. It is a building block of the risk assessment. _Which groups are considered particularly vulnerable?_ For heat, mainly very elderly people, the chronically ill, infants and small children, pregnant women, and people who work outdoors or are homeless. Social factors such as isolation or language barriers add to this. _Is the use of residents' register data compliant with data protection?_ Yes, provided you evaluate the data in aggregated form and without personal reference, for example as an age share per statistical district. Clarify the specific approach with your data protection officer. _How often should exposure be updated?_ Every few years or in the event of major changes: new development areas, new care facilities, updated climate data. Exposure is not static.

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