Air Quality

iSCAPE Citizen Science Workshops Air Quality Data

Air-quality sensor data (temperature, humidity, PM, noise, light) collected in citizen science workshops across 6 European cities: Vantaa, Dublin, Bologna, Bottrop, Hasselt and Guildford.

Size
147.1 MB
Format
CSV, YAML
License
CC0-1.0
Access
Open Access
Source
Zenodo (record 3570680)

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Challenge

Do the six iSCAPE workshop cities share a daily rhythm in air pollution and street noise -- is there a common rush-hour signal, or does each city march to its own beat? And which city breathed the cleanest air during its workshop?

Where to start
There is no city column. First read the six test_description_*.yaml files to map each <id>.csv (a sensor kit) to its city and timezone (the 'location' field, e.g. Europe/Dublin). Then load just Time, EXT_PM_25 and NOISE_A from every kit with pd.read_csv(usecols=...), parse Time with pd.to_datetime(..., utc=True) and tz_convert to each city's local time so the hour-of-day is comparable. Group by city and local hour to build per-city daily profiles.
What to share
An hour-of-day profile of PM2.5 and/or NOISE_A comparing all (or several) cities -- e.g. overlaid line charts or a city x hour heatmap -- plus a short note on what is shared (a traffic-like morning/evening bump) versus local, and a ranking of cities by typical PM2.5 against the WHO 15 ug/m3 guideline, caveated by the very uneven data coverage between cities.

💬 Discuss this dataset, ask questions and share your results in its discussion thread. Challenges are open-ended — there's no single right answer.