Analysis: Researchers using Google Street View air quality data can pinpoint the parts of the city with the biggest concentrations of pollutants
By David O’Connor, DCU and Jiayao Chen, UCD
Dublin’s air quality has long been shaped by its dependence on fossil fuels. Coal and turf burned for heating once blanketed the city in a dense smog during colder months, creating health crises that became all too common by the mid-20th century. Regulations introduced in the 1990s, including the ban on smoky coal, marked a turning point and gradually helped to clear the air.
While solid fuel burning is still a problem, additional challenges have arisen. Today, nitrogen dioxide (NO₂) and fine particulate matter (PM₂.₅) from vehicle exhausts are the main culprits, posing significant health risks in densely populated and traffic-heavy areas. Poor air quality contributes to approximately 1,300 premature deaths in Ireland every year.
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From RTÉ Radio 1’s Morning Ireland, the EPA’s Roni Howe discusses its 2023 Air Quality report and why it’s calling on local authoritirs to ban the sale of smoky fuels
Fortunately, emerging technologies like hyperlocal air quality monitoring offer new ways to tackle these evolving pollution issues. Cities like Dublin can now leverage real-time, street-by-street data to understand and address the specific sources of pollution. A recent Google Street View initiative, Google Air View, exemplifies this progress, mapping pollution hotspots across Dublin and providing actionable insights that could transform urban health policies and improve the quality of life for all residents.
What is hyperlocal monitoring?
Hyperlocal air quality monitoring uses advanced mobile sensor technologies to measure pollution giving unprecedented insights about where and when it is occurring. In cities around the world, Google’s fleet of all-electric Street View vehicles has been fitted with high-grade sensors to record pollutant concentrations across dense urban landscapes, providing an insightful layer of data on how air quality changes from street to street and minute by minute.
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From Google, how the company’s Street View vehicleds are mapping air quality in Dublin
By pinpointing specific areas and times of day when pollution spikes, hyperlocal data empowers cities to create targeted, real-time responses to pollution sources. In addition, hyperlocal data can be integrated into urban planning tools and health models, helping city planners identify pollution-heavy zones near schools, hospitals, or densely populated communities and it gives cities the tools needed to create cleaner, healthier, and more equitable urban environments.
Dublin’s air quality landscape
Researchers from DCU and UCD analysed data collected over a 12 month period, with Google Street View vehicles covering different parts of the city on weekdays from 7am to 7pm. We collected over 5 million data points on key pollutants across road segments in Dublin, allowing us to map pollution intensity with unmatched precision.
The data showed that 49.4% of days during the sampling period exceeded World Health Organisation (WHO) guidelines for NO₂ levels, with peaks during rush hours, especially in winter. The study pinpointed several NO₂ and PM₂.₅ hotspots in Dublin, such as O’Connell Street, Cork Street and the vicinity of Dublin Port, underscoring the contribution of vehicular and industrial emissions
Insights from other Google air quality studies
Dublin’s findings echo patterns observed in other cities studied through Google Street View’s air quality monitoring. In Oakland, California, for instance, a similar mobile monitoring study revealed striking variation in pollution levels across districts within the city. Researchers found that communities near motorways or industrial zones were exposed to substantially higher levels of NO₂ and PM₂.₅, often with concentrations up to three times higher than in less congested areas. These high pollution levels have direct implications for residents, who experience higher rates of asthma and other respiratory illnesses
It’s no great surprise that the Dublin study found NO₂ levels peaked during morning and evening rush hours, with greater concentrations in winter. These temporal trends underscore the role of traffic emissions and meteorological factors in urban pollution, suggesting that pollution-reduction measures could be intensified during high-risk periods.
How could this shape pollution policy for Dublin?
Hyperlocal data from Google’s studies can guide cities like Dublin in implementing targeted pollution-reduction policies. The detailed maps produced by the study highlight specific areas where interventions could be most effective. In particular, establishing Low Emission Zones (LEZs) around identified hotspots could limit high-emission vehicles and incentivise the transition to cleaner forms of transportation.
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From RTÉ Radio 1’s News At One, Prof Brian Caulfield from TCD on London’s introduction of new Ultra Low Emission Zones where owners of the most polluting vehicles pay a charge to drive anywhere in the city
Dublin could also prioritise investments in green infrastructure in pollution-prone areas to help absorb pollutants and improve air quality. Additionally, using real-time pollution data to manage traffic flow during peak hours could reduce exposure to harmful pollutants.
Drawing on Amsterdam’s response to a similar study , Dublin could explore incentives for electric vehicle use and prioritise public transit and cycling infrastructure in high-pollution areas. Amsterdam’s expansion of electric vehicle charging stations (with over 20,000 installed in the last few years) and its shift towards electric public transit offers a model for how cities can leverage policy to mitigate pollution while supporting sustainable urban development.
Localised air quality data can produce policies to tackle pollution at its source, particularly in high-risk and vulnerable areas
The integration of hyperlocal monitoring through initiatives like Google Air View represents a major advance in urban air quality management. By capturing real-time, location-specific data, cities gain the insights needed to make informed decisions that protect public health and promote environmental equity.
Studies in Dublin, Oakland, and Amsterdam demonstrate the effectiveness of this approach in identifying pollution hotspots, understanding the sources and patterns of pollution, and guiding policy interventions. Localised air quality data provides the foundation for tailored, evidence-based policy solutions that can tackle pollution at its source, particularly in high-risk and vulnerable areas.
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Dr David O’Connor is Assistant Professor in the School of Chemical Sciences at DCU. He is a Research Ireland awardee. Dr Jiayao Chen is a Research Fellow in the School of Architecture, Planning and Environmental Policy at UCD
The views expressed here are those of the author and do not represent or reflect the views of RTÉ
