Trust in every reading
Our mission is to make air quality data accessible, transparent, and actionable, but none of that is possible without trust. At Airly, we invest in quality at every stage: from production and deployment, to real-time monitoring and calibration.
Whether you're a policymaker, business leader, or concerned citizen, you can count on Airly sensors to deliver data that’s both scientifically sound and independently verified.
Certified and validated
Airparif
of Sciences
AQMD
Our certifications
- CE- & UKCA-compliant
- GPSR-compliant
- ISO-certified production facility
- MCERTS certification for PM2.5 and PM10
Independent validation
Our technology is regularly validated by respected independent institutions, academic bodies, and research centres. Recent studies confirm the significant improvement of our sensors over time, proving our commitment to continuous innovation.
Organisations that have validated or reviewed Airly sensors include:
- Afri-SET (Ghana)
- AGH University & GIOŚ (Poland)
- Airparif (France)
- Flemish Institute for Technological Research (Belgium)
- IPIŚ PAN (Poland)
- Ricardo (UK)
- South Coast AQMD (USA)
Why sensor accuracy and precision matter?
At Airly, we believe that the fight against air pollution starts with reliable data. Our mission is to deliver accurate, real-time insights that empower cities, businesses, and communities to make informed decisions and drive meaningful action. The foundation of this effort lies in the quality of our air quality data.
Not all sensors are created equal. Many low-cost solutions available on the market suffer from inferior accuracy, inconsistent readings, and poor reliability. This leads to mistrust among users and can ultimately hinder efforts to reduce pollution. That’s why Airly has made sensor accuracy, precision, and quality assurance a top priority.
Benefits
Scientific accuracy
Airly sensors deliver data accuracy close to regulatory reference standards, which ensures users can rely on scientifically sound data even in complex urban environments.
Rigorous quality control
Every sensor undergoes strict quality assurance, and is subject to continuous remote calibration and network monitoring. This end-to-end process guarantees long-term reliability and minimizes sensor drift.
Independent validation
Airly’s technology is independently validated by leading institutions across Europe, Africa, and the US, confirming its credibility and performance in diverse real-world conditions.
Proven in the field:
co-location studies
To verify sensor performance in real-world conditions, Airly conducts co-location studies across various geographic and environmental conditions.
Show tests results:
Co-location studies report
Download the full pollution report. Give us your email address so that we can send you a report.
Build your ideal air quality monitoring setup
High-quality, end-to-end system
Precision starts in production
Every Airly sensor goes through a rigorous and certified production process. Manufacturing takes place at an ISO-certified facility, with final assembly, quality assurance process and calibration completed in our own laboratories.
Only devices that meet our stringent standards are approved for shipment and deployment.
Before shipping, each sensor undergoes strict quality assurance procedures, including:
Verification of performance against signal strength, accuracy, and stability criteria.
Co-location with certified reference analyzers meeting Fixed Measurements criteria following Directive (EU) 2024/2881 of the European Parliament and of the Council of 23 October 2024 on ambient air quality and cleaner air for Europe.
Sensor-to-sensor and sensor-to-reference comparison using advanced lab and field testing setups.
Uncertainty and standards compliance
Airly sensors deliver accuracy close to regulatory reference standards. Our performance for PM2.5, PM10, NO2, and O3 meets the Class 1 criteria of the European standard CEN/TS 17660, ensuring precision even in complex urban environments (with MCERTS certification serving as confirmation for PM 2.5 and PM10 accuracy).
We also comply with the PAS 4023 specification for the deployment and quality control of low-cost air quality sensors in outdoor ambient air.
How we maintain the highest quality
Advanced QA/QC procedures
Our quality control does not stop after installation. Airly uses automated network monitoring tools to continuously:
- Identify anomalies or hardware failures
- Detect irregular data patterns (e.g. repeated values)
- Identify out-of-range values
We also integrate data from reference analysers (EEA, US EPA and others) into our systems to double-check the quality of our sensors against reference methods.
Most issues can be resolved remotely through device restarts, manual expert review of data and device status, or recalibration.
In rare cases where remote troubleshooting is not sufficient, we work with our customers to analyse root causes and replace the sensors. The replaced hardware is analysed to prevent future failures.
Additionally, our Data Science team regularly reassesses the entire network to maintain consistency and reliability.
Ongoing dynamic calibration
To ensure data quality over time, we use advanced, dynamic calibration processes:
- For particulate matter data - to account for shifts in environmental conditions, we apply a monthly calibration based on data from our reference station co-locations. This delivers greater accuracy and reduced uncertainty.
- For gas measurements - To correct for factors such as cross-sensitivity with other gases, the impact of weather conditions, and sensor drift, we apply advanced real-time algorithms. This improves the quality and consistency of our data.
When our sensors are co-located with a reference station (authorised by environmental authorities) - which we recommend for new installations - we can take our calibration to the next level and adjust our readings to local conditions (following recommendations from CEN/TS 17660). This is the most robust calibration method available.
Airly does not use air quality modelling or machine learning techniques to “predict” air quality levels due to the lack of traceability, transparency, and robustness of these methods.
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