Introducing Network QAQC: Real-Time Confidence in Zephyr Networks

David Green
May 22
3 min read

In our first blog, Why Data Quality Matters in Indicative Air Quality Monitoring, we explored the rising importance of indicative sensors in air quality management and the critical need to ensure the data they produce is trustworthy. We discussed the challenges inherent to sensor-based systems—such as cross-interference, drift, and sensitivity to humidity—and highlighted how calibration, algorithmic correction, and validation are key pillars in maintaining data integrity.

While initial QAQC measures—such as pre-deployment calibration and lab-based verification—are vital to establishing a strong baseline for performance, there are scenarios where real-time confidence in data quality is essential. Whether influencing public health decisions, triggering mitigation responses, or feeding into live dashboards, some use cases simply can’t wait for post-hoc validation.

To meet this need, EarthSense introduces Zephyr® Network QAQC—a real-time correction framework that ensures data across the network is not only traceable and comparable but also actively corrected using linear factors derived from co-located Zephyrs. This innovation helps ensure consistent, high-quality data across wide geographies and evolving environmental conditions.

Benefits of Network-Wide QAQC for Indicative Monitoring

A Zephyr network enhanced with real-time QAQC provides users with confidence in data comparability and accuracy—meeting the expectations of indicative performance standards such as CEN/TS 17660 and indicative MCERTS. But the benefits go beyond compliance.

Networks with known uncertainties are invaluable in the long-term screening of urban areas, helping to:

Identify pollution hotspots
Validate air quality models
Support the early stages of Local Air Quality Management (LAQM)

Crucially, when sensors report consistent, corrected values across locations, local authorities and decision-makers can make informed interventions with real-time awareness. This is especially important for temporary mitigation strategies, behavioural change campaigns, and evaluating the impact of local transport or planning policies.

Ultimately, a network that knows its uncertainties—and corrects for them—adds value not just to the dataset, but to the insights and actions that follow.

Inter-Instrument Uncertainty: Ensuring Network Comparability

When applying a network-wide correction factor, one of the most important prerequisites is inter-instrument consistency. If sensors vary significantly in how they respond to the same conditions, the integrity of a shared correction model could be undermined.

This is why EarthSense performs inter-instrument uncertainty assessments as part of its QAQC process. Zephyrs are co-located in controlled conditions, allowing us to quantify variation across instruments. From this, we can:

Apply factory calibrations based on field-tested behaviours
Determine inter-instrument uncertainty for all sensors in the network
Ensure only Zephyrs that meet the CEN/TS 17660 or indicative MCERTS standards are deployed

This approach ensures a high level of comparability between units, making it possible to reliably compare data from different locations across a city, region, or transport corridor.

Local Correction Factors: Real-Time Confidence with Transparent Methods

Real-time QAQC is not about erasing sensor limitations—it’s about enhancing confidence in the data through transparent, evidence-based correction. This is where local correction factors come into play.

Derived from co-located deployments with reference instruments, local correction factors provide a simple yet powerful method for adjusting sensor output in real time.

The process works as follows:

Cleansing – Raw, calibrated Zephyr data is filtered to remove erroneous or unstable measurements.
Comparison – The remaining data is compared against Quality Assured reference measurements over a period that captures natural fluctuations in meteorological conditions, with comparisons performed on an hourly basis to support timely and responsive corrections.
Linear correction – A slope and offset are calculated via linear regression and applied across the network to all calibrated Zephyr data, producing consistently corrected values and ensuring comparability throughout the sensor fleet

This approach allows the initial calibration coefficients to remain static, maintaining traceability and auditability, while refining output for improved accuracy.

While real-time correction delivers high-quality outputs for immediate use, particularly valuable for behaviour change initiatives, active mitigation, and live reporting, some applications—such as formal annual reporting or compliance assessments—benefit from additional verification. For these cases, EarthSense offers annual data ratification servicesas an add-on, providing an extra layer of confidence by validating Zephyr data against reference measurements once those reference datasets have been fully quality assured. This ensures your network not only performs in real time, but also supports long-term reporting with traceable, ratified data.

Zephyr QAQC: Available Now for All Networks

Whether you're operating a newly installed network or managing an existing deployment, EarthSense can now provide real-time QAQC for Zephyr networks of any size and age. Our approach enhances not just the precision of individual units, but the overall reliability and comparability of the entire sensor fleet.

Next in this blog series, we’ll be Explaining the Performance Standards—demystifying what CEN/TS 17660, ASTM D8559-24, and PAS4023 mean for indicative sensor users, and how to interpret and apply them effectively in real-world scenarios. Following that, we’ll showcase how our Network QAQC approach is delivering real-world value in a case study with West Midlands Combined Authority, where it’s supporting real-time decision-making and long-term air quality policy development.