How the New Zealand National Institute of Water and Atmospheric Research informs policy and public health with hyperlocal air quality mapping

NIWA has pioneered the use of dense air quality sensor networks to uncover block-by-block air pollution patterns within towns across New Zealand.

A Node-S air quality sensor deployed to monitor air pollution trends in New Zealand.
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Clarity Node-S solar-powered air quality sensors deployed

3x

Higher PM2.5 levels detected in air pollution hotspots compared to cleanest areas

6 km

Maximum distance NIWA deployed Clarity sensors downwind to capture pollution plumes

Dr. Ian Longley

Dr. Ian Longley

Principal Scientist - Air Quality, National Institute of Water and Atmospheric Research
"We needed high-density data to develop a model that was representative of a real situation on a very local scale – so multiple devices and multiple locations. The Clarity Node-S was ideal for this use case."

Across New Zealand, outdoor air pollution poses a significant yet often invisible threat to public health. To confront this silent killer, scientists at the National Institute of Water and Atmospheric Research (NIWA) have turned to a powerful ally — hyperlocal air quality mapping, powered by compact solar-charged air quality sensors.

As Principal Scientist for Air Quality, Dr. Longley has pioneered the use of dense air pollution sensor networks to uncover block-by-block air quality patterns within towns. By peering into this localized variability, the resulting maps provide actionable insights to enhance air quality policymaking, forecasting, modeling, and public health.

Challenges Of Sparse And Static Air Quality Monitoring

Historically, New Zealand has relied on a sparse network of reference-grade air quality monitoring stations, with just one station covering most towns. But as stations can’t always be located within residential areas, or capture differences between neighbourhoods, this monitoring provides limited visibility into true neighbourhood-level exposures.

According to Dr. Longley, "We needed high density of data to develop a model that was representative of the real situation on a very local scale — so multiple devices and multiple locations."

In addition, the static positioning of these reference stations makes it difficult to respond to emerging air pollution hotspots. With air pollution sources ranging from industrial emissions to dust storms, flexibility in repositioning air quality monitors is critical.

Empowering Hyperlocal Air Pollution Mapping With Solar-Powered Air Quality Sensors

To overcome these challenges, NIWA deploys compact, solar-charged air quality sensors that require no external power or hardwired internet.

NIWA technician Duncan Holland installs a Clarity Node-S to measure air quality in a residential neighborhood. These air quality sensors can be installed in minutes and are easily mounted to existing infrastructure such as streetlamp posts. 
We work mainly with the local authorities for deploying the Node-S devices — with the local council. But the additional involvement of local members of the community has been really helpful and has made a big difference in getting coverage where we need it quickly and efficiently." 

— Dr Ian Longley, Principal Scientist - Air Quality at NIWA

The robust, weatherproof Clarity Node-S devices can be mounted to street poles and traffic lights to create air quality sensor grids covering entire towns. With integrated cellular connectivity, the units continuously stream real-time air quality data to the Clarity Dashboard, where NIWA can review data and manage their network.  

With the Clarity Dashboard, NIWA can easily review real-time and historical data from their air pollution sensors to identify air quality trends. 

Within hours, a single air quality technician can deploy an air quality sensor network comprising dozens of devices throughout a community. Compared to the sparse reference stations, this approach provides unprecedented hyperlocal air pollution mapping capabilities.

A deployed Clarity Node-S air pollution sensor measures air quality in a residential neighborhood — providing real-time, accurate air quality data to the local community. 

The visually compelling maps that emerge from this dense air quality monitoring reveal otherwise hidden air pollution hotspots, pathways, and trends. Beyond informing air quality modeling and forecast efforts, the localized visibility provided by the sensor networks helps catalyze community awareness and policy response.

NIWA scientists deploy Clarity Node-S devices in tight grids across multiple urban areas, large and small.

By making the invisible threat of air pollution visible and real for residents, the need for change becomes difficult to ignore. Citizens can see how localized sources ranging from industrial emissions to residential wood smoke move across and impact their neighborhood’s air.

In one project, NIWA deployed over 40 Clarity sensors to map wintertime woodsmoke pollution across a town. The resulting real-time data and pollution maps are providing insights to inform the development of New Zealand's first nationwide residential woodsmoke forecasting model.

We couldn’t have done this type of hyperlocal monitoring with static reference-grade stations. The low-cost sensors allowed us to adaptively map pollution and inform modeling efforts.”

— Dr Ian Longley, Principal Scientist - Air Quality at NIWA

Responding To Emergencies And Engaging Communities

In addition to everyday air quality mapping, NIWA has utilized air quality sensor networks for emergency responses. After severe flooding impacted agricultural areas, dried silt deposits led to dangerous dust storms.

NIWA rapidly deployed dozens of Clarity Nodes to monitor the dust impacts. The real-time air pollution data is informing the development of air quality forecasting models to predict future dust storms related to climate events.

A Node-S air quality sensor measuring the air quality impacts of dust pollution in an agricultural area. 

Dr. Longley explains this project also produced an unexpected benefit: “What's inadvertently happened is it's become a community resilience project by accident.”

By collaborating directly with residents to install sensors, the effort strengthened community engagement and reciprocity. Thanks to the democratizing potential of compact air quality sensors, a country known for its clean air is pioneering new ways to understand localized air pollution and protect at-risk communities.

As Dr. Longley summarizes, “The community has been really helpful and has made a big difference.”

Lasting Impact On Policy And Public Health

The hyperlocal air pollution data unlocked by dense air quality sensor networks is already informing emission reduction policies and enabling targeted public health interventions for NIWA — but the greatest impact may be ahead.

We’re at the start of a new era where compact low-cost sensing allows us to uncover previously invisible air pollution patterns. These insights can help us continually refine air quality models, forecasts, and policies over time. But most importantly, they will empower communities to play an active role in confronting and improving their local air quality.”

— Dr Ian Longley, Principal Scientist - Air Quality at NIWA

By shining a spotlight on previously overlooked air pollution trends, innovative scientific institutions like NIWA are partnering directly with towns and neighborhoods to pioneer localized air quality solutions. In the process, they are lifting the veil on air pollution’s silent threat to enhance public health protections across New Zealand.

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