Pollenwarte

Inspiration

A bright morning tells us very little about what is in the air. For people who react to pollen, the day starts with questions: which species are present, when does the forecast ease, and how does that compare with how I feel?

Pollenwarte turns those questions into a personal field guide. Its identity brings together two kinds of observation: reading the air and recording your own story.

What it does

Pollenwarte presents European hourly pollen forecasts, species details, and quieter forecast windows. A symptom diary records severity and notes; analysis compares those entries with modelled pollen values to reveal possible patterns.

The lexicon introduces pollen species through microscopy-inspired grain illustrations and sourced articles. Pollenwarte Plus adds a geographic pollen heatmap. Forecasts, the diary, analysis, and lexicon remain free.

Missing values are shown as unavailable. Cached forecasts retain their age. Personal patterns are clearly described as observations, not diagnoses.

How we built it

We built the app with Flutter and Dart, Riverpod, Dio, and Hive. European hourly values come from Open-Meteo's CAMS data; the German Weather Service provides additional pollen-index context. Google Pollen powers the paid heatmap.

RevenueCat manages monthly and annual Plus subscriptions. The iOS Home Screen widget uses SwiftUI and WidgetKit. German, English, French, and Italian interfaces share the same product structure.

Challenges we faced

The hardest problem was keeping different kinds of data honest. Hourly concentrations, daily indices, cached values, and personal diary entries each mean something different. We preserved their units, timestamps, and source context rather than presenting them as interchangeable.

We also worked to make a detailed forecast approachable through clear species rows, hourly ribbons, readable typography, and explanations close to the numbers.

What we learned

Trust comes from showing what a number means, where it came from, and what it cannot establish. A missing value needs an honest empty state; a correlation needs a careful explanation.

Pollenwarte's purpose is to help people understand their day through observation. Read the air. Write your story.

Built With

• api
• carto
• dart
• dio
• dwd
• flutter
• google
• hive
• open-meteo
• openstreetmap
• pollen
• revenuecat
• riverpod
• swiftui
• widgetkit