Features

ACCURACY
Designed for type approval & certification
Easy Installation
Set up and installation with experienced O&M team
REAL-TIME DATA
Access to your data and alarms in real-time
Scalability
Easily add multiple hyperlocal sensors
Clusterbased approach
Adjust the baseline and span remotely
Spatio-temporal resolution
Increased spatial resolution of air quality data

Acoem hybrid air quality monitoring

Acoem’s Hybrid Air Monitoring Network combines the world’s finest hyperlocal sensors — the Kunak AIR Pro —  with Acoem’s trusted range of ambient air quality monitors with Serinus® gas analysers. Together, they can transform the way smart cities and progressive thinking organisations use the power of collective environmental monitoring to measure, report and adhere to air quality standards and regulations.

The hybrid network — with reference-grade traditional air quality stations supported by the deployment of multiple sensor-based air quality monitors — supplements any localised data gaps in the CAAQMS’ measurements by incorporating spatially dense data inputs.

Kunak AIR Pro hyperlocal sensors are installed in ideal proportion around reference monitoring systems to form a hybrid air monitoring cluster. This cluster-based approach to establishing a hybrid air monitoring network at a city scale ensures accurate environmental data collection with higher density.

Hybrid air quality monitoring networks: strength through unity

Enhanced data quality & spatiotemporal resolution

Hybrid networks integrate the reliability and precision of reference stations with low-cost sensor-based devices to provide a robust and thorough hyperlocal view of air quality at any point in time. They yield enhanced data quality and spatiotemporal resolution compared to individual monitoring systems.

Carefully designed hybrid monitoring networks offer invaluable data that identifies hyperlocal pollution hotspots and accurate pollution heat maps. High density precise environmental data can be used to create high-resolution air quality models that consider the effect of pollution sources and meteorological conditions.

For example, changes in wind direction and strength and temperature fluctuations have a significant effect on pollution levels. So too do environmental phenomena like volcanic eruptions and bushfires. The ability to isolate influencing factors removes a level of uncertainly. The networks also aid in defining and designing more efficient regulatory monitoring networks.

 “Combining real-time hyperlocalised monitoring with traditional reference quality monitoring and accurate predictive modelling is the most effective way to plan intervention strategies and effectively manage air quality.”

Scalability

When multiple hyperlocal sensors are used together, they deliver localised real-time air quality data that supports initiatives to reduce air pollution and its risk to human health.

It’s this ability to easily add, subtract or relocate individual sensor pods where and when required that provides environmental professionals with a level of monitoring flexibility and scalability not possible with fixed-site reference quality CAAQMS alone. They can be used for diverse applications, which may range from urban background monitoring to exposure level monitoring.

Cluster based approach

Strategically placing a high number of hyperlocal sensors around and between a low number of reference quality CAAQMS systems delivers hyperlocal monitoring results.

However, micro-sensor technology is not a direct substitute for reference quality instruments, especially for mandatory or regulatory purposes.

That is why when Kunak AIR Pro is used as a complementary source of information to augment and enhance existing reference quality CAAQMS networks, environmental professionals are rewarded with increased spatial resolution of air quality data. Increased spatial resolution of air quality data dramatically multiplies the opportunity for better understanding, insight and action.

 

Bridging the gap

Pollution heat maps and odour impact maps generated by dispersion models provide hyperlocal pollution concentration. With real-time air quality monitoring, these maps can also be generated and updated in real-time. However, the number of datapoints which is required for such exercises is very high for traditional monitoring stations to achieve.

Sensor-based real-time monitors bridge this gap while traditional monitoring acts as a reference station. The sensor-based device is constantly collocated, calibrated and corrected against the reference station, ensuring the highest accuracy of data quality. A hybrid network provides optimal-quality hyperlocal pollution measurement a higher spatial resolution of air quality data.

Applications

Hybrid air quality monitor solutions are one of the best ways to extend air quality monitoring in environments as heterogeneous as urban areas, where various emission sources are concentrated.

Resources

Hybrid Air Monitoring Network
Brochure Hyperlocal Air Monitoring Sensors
Spec Sheet

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Case studies

It is a sensor-based air quality monitoring solution designed for easy installation, operation, and maintenance while maintaining an accurate measurement of the pollutants to be measured.

Our business cases
Acoem’s role in helping Thailand monitor air quality as part of its COVID-19 response By Aslam Rangparia Air quality monitoring
Air Samplers for Environmental Monitoring By Aslam Rangparia Air quality monitoring

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