Prove your interventions work with state-of-the-art science
RHEA
Evaluates whether air quality interventions actually work, using rigorous statistical methods that stand up to scrutiny.
Edinburgh's LEZ cut evening rush NO2 by 6.6 µg/m³
RHEA's diurnal fingerprinting detected a statistically significant traffic-pattern effect (p = 0.006) that simpler methods miss. See the full analysis.
Local authorities invest millions in Low Emission Zones, school streets, and traffic management — but proving these interventions actually improved air quality is surprisingly difficult. Weather variation, seasonal cycles, and regional trends can all mask or mimic a real effect.
RHEA uses difference-in-differences analysis — comparing treatment and control monitoring sites before and after an intervention — with block bootstrap inference for honest uncertainty estimates. Its distinctive feature is diurnal fingerprinting: breaking effects down by hour of day to check whether changes follow the time patterns you’d expect from the mechanism.
The Edinburgh LEZ is a good example. A simple before-and-after comparison shows a modest decline, but RHEA’s hour-by-hour analysis reveals the real story: the drop is concentrated in the 4pm–6pm evening rush, exactly when traffic restrictions should have the most effect.
Capabilities
- Difference-in-differences analysis with block bootstrap inference
- Diurnal fingerprinting to detect time-of-day effects
- Random Forest deweathering to isolate intervention signal
- Interactive monitoring network explorer
- Power-aware sensor placement optimisation
- Pre-loaded case studies for Scottish and English LEZs
Interested in RHEA?
RHEA is in active development. Get in touch to discuss early access.
Get in touch