Air Quality Sensor Networks for Evidence-Based Policy Making: Best Practices for Actionable Insights

(1) Background: This work evaluated the usability of commercial “low-cost” air quality sensor systems to substantiate evidence-based policy making. (2) Methods: Two commercially available (Airly, Kunak) were benchmarked at a regulatory monitoring station (AQMS) and subsequently deployed in Kampenhout Sint-Niklaas (Belgium) address real-world concerns: (a) what is pollution contribution from road traffic near school central city square (b) do local interventions result quantifiable impacts? (3) Results: The considered performed well terms data capture, correlation intra-sensor uncertainty. Their accuracy was improved via re-calibration, up levels for indicative measurements as set Air Quality Directive (Uexp < 50% PM <25% NO2). A methodological setup proposed using background source locations, allowing quantification (3.1) maximum potential impact (3.2) impacts different with reductions 89% NO2 60% NO throughout 3 month period; (4) Conclusions: Our results indicate that are able accurately quantify (even short-lived) measures contribute making under condition proper (background normalization) (recurrent calibration) procedure. applied methodology learnings distilled blueprint networks replication actions other cities.