Full whitepaper here: https://oizom.com/white-papers/hybrid-air-quality-monitoring-network/ Rapid urbanization, industrialization, and a rise in vehicular pollution have severely affected air quality in cities. With growing concerns about air pollution and cascading effects across the population, air pollution is emerging as a significant problem. Vehicular pollution, road dust, construction, and industrial pollution are some of the major sources responsible for air pollution in Indian cities. Urban air quality is particularly difficult to measure owing to highly heterogeneous pollution distribution. Therefore, it is very crucial to create a dense air quality monitoring network in order to effectively record the spatial variation of pollutant concentration. Monitoring air quality at such a scale with (first and second generation) continuous ambient air quality monitoring stations (CAAQMS) is very expensive. As a result, they are not deployed at a spatial density sufficient for measuring air quality with high spatiotemporal details. In recent times, low-cost sensor-based systems have evolved as a highly reliable and scalable solution for real-time ambient air quality monitoring. However, calibration is crucial for sensor accuracy. Hybrid air quality networks provide the best of both worlds. It is a network of air quality monitors in which traditional air quality stations are supported with the deployment of multiple sensor-based air quality monitors. The hybrid network complements the data gaps of CAAQMS by incorporating spatially dense data inputs from low-cost sensor-based air quality monitors. This paper explains hybrid air quality monitoring networks and how to design and develop it. It also serves as a guide for setting up a hybrid monitoring network. Such a hybrid network with densely located monitors are capable of providing air pollution information at the spatial resolution as good as 100 x 100 m. Hybrid monitoring network serves all the stakeholders of urban air quality. It is a very economical and effective approach of air quality monitoring and can be easily implemented at any urban location. It significantly improves the capacity of any urban air quality monitoring scheme.

1. HYBRID AIR QUALITY
MONITORING NETWORK
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2. INTRODUCTION
Rapid urbanization, industrialization, and a rise in vehicular pollution have severely affected air quality in cities.
Urban air quality is particularly difficult to measure owing to highly heterogeneous pollution distribution.
Therefore, it is very crucial to create a dense air quality monitoring network in order to understand the spatio-
temporal variations in pollutant concentration.
Hybrid air quality monitoring network
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+ +
Hybrid Ambient Air
Quality Monitoring

3. NEED OF HYBRID NETWORK
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Hybrid air quality monitoring network
A hybrid network of air quality
monitors consists:
traditional ambient air quality
monitors - reference stations
sensor-based monitors - spatially
dense data generation points
They are cost-effective, high quality
air quality monitoring approach.

4. SCALABILITY
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Hybrid air quality monitoring network
Reference stations are ineffective in scalability and
flexibility due to their inadequate spatio-temporal
resolution.
Hybrid networks are highly scalable by their design.
They can be used for diverse objectives, which may
range from urban background monitoring to
exposure level monitoring.

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COST
National Clean Air Programme (2019)
Measure air quality of majority of towns and cities across India.
Existing Monitoring Stations:
134 CAAQMS and 703 manual operating stations.
Hybrid monitoring by integrating all the monitoring systems
with low-cost sensors will prove more efficient, accurate, and
economic.
It is very expensive to match the spatial scale and density of
sensor-based monitoring systems with traditional systems.
Hybrid air quality monitoring network

6. HYPERLOCAL POLLUTION MAPPING
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Hybrid network of air quality monitors hyperlocal
pollution measurement at significantly low cost.Pollution heat maps and odour impact maps
generated by dispersion models.
With real-time air quality monitoring, real time
maps can be generated.
High Quality Data:
The sensor-based device is constantly collocated
and corrected against the reference station.
Hybrid air quality monitoring network

7. CALIBRATION AND COLLOCATION
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USEPA recommends collocating sensor-based
systems with reference systems to correct data
drift and measurement bias.
With such a hybrid network, the limitations and gaps of
traditional monitoring stations are complemented and hyper-
local air quality data can be generated.
This ensures constant QA / QC for sensor-based
systems and provides the highest level air quality
data.
Hybrid air quality monitoring network

8. SETTING UP A HYBRID NETWORK
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Reference Station :
Oizom Sensor-Based Systems
1 : 12
Each cluster : 25 sq. km
Satellite
Data
Traffic
Data
Meteorological
Data
Secondary Data for high resolution
(100 x 100 m) pollution map
Hybrid air quality monitoring network

9. BENEFITS
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Stakeholders
Involvement of Individuals, Corporates as well as
Industries will benefit the clean air plans with the
help of such novel methods of air quality
monitoring.
Tax Payers – Citizen
A hybrid network helps in achieving
better public health. Actionable
insights for better healthcare can be
taken by the public.
Tax Payers – Industries and Businesses
With a better understanding of the air quality,
businesses and industries can attract better
employability, improve health and safety
City Planners
Strategic developments by placing high sensitive
infrastructure.
Regulators
The Central and the State Pollution
control boards are the key enforcers of
environmental laws. Hyper-local data
helps in the identification of hot spots &
source apportionment studies.
Policymakers
Useful data helps to fill knowledge
gaps and provides a robust platform for
policy advocacy, assess policy goals
and targets which are likely to be met.
Urban Local Bodies (UBL)
Real-time monitoring of the city's air quality will
contribute to the city level Clean Air Plans and
policies.
Hybrid air quality monitoring network

10. OIZOM’S OFFERING
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Easy Integration to existing and new
Reference Stations.
A visual representation of a typical hybrid network
for the city of Ahmedabad(India)
Better Data Quality and Calibration
through Machine Learning algorithms:
Easy collocation
Remotely and at the site (reference station)
Hybrid air quality monitoring network