Clean air is vital for life on Earth. Yet, 99% of the global population breathes air exceeding WHO guidelines. We can fix air pollution through the massive adoption of sustainable behaviors and by collecting, analyzing, and acting based on hyperlocal air quality data.
Why hyperlocal air quality data? Keep reading this blog post to learn why it is so important to solve air pollution.
Hyperlocal air quality data is street-level information about the air quality that is collected through monitoring systems/devices. Air quality data precision on this level is very important due to the fact that in densely populated urban areas air quality can drastically change from one street to another. The air quality in a narrow street with tall buildings will most likely be very different from the air quality in a broad and open one – even if they are only a few meters apart.
In such cases, hyperlocal data can be used to understand the local air quality and identify potential sources of pollution. It can also be used to inform decisions about how to improve air quality in the area and to monitor compliance with air quality standards.
The devices that collect data are often part of a vast and dense network and use sensors to measure different air pollutants, such as nitrogen dioxide and ultrafine/fine particles of different sizes.
Although the individual behavior and education of peers are essential, the two main drivers for change in air quality are public organizations and businesses. Having access to hyperlocal air quality data provides significant benefits to both.
For local governments and environmental agencies, this data can help them identify air pollution hotspots and focus their efforts on mitigating air pollution in those areas.
Having this data allows them to act quickly on any immediate air quality hazards and plan for future infrastructure projects that could improve air quality. It can also help inform policy decisions, such as the creation of air quality standards or the implementation of incentives for businesses to reduce emissions.
With access to accurate and timely data, governments can ensure that citizens are better informed and protected from the dangers of air pollution. Finally, having hyperlocal air quality data can provide economic benefits, as it can help generate more accurate estimates of the cost of pollution mitigation measures, as well as improve the decision-making process on which areas are most suitable for investment.
For businesses, having hyperlocal air quality data delivers valuable insights into their operations, allowing them to analyze their impact on the surrounding environment and make changes to reduce their emissions. This data can be used to inform decisions about where and how to locate new factories or other operations for example.
Businesses from different sectors can also use hyperlocal air quality data to protect their users. For instance, smart mobility and location-based services can add street-level air quality data to their products to safeguard their users from hazardous pollutants and help them achieve healthier lifestyles by navigating the cleanest routes.
Learn more about how hyperlocal air quality data adds value to businesses.
With the right investments and resources, it is possible to obtain highly accurate and timely data that can greatly benefit local communities, citizens, businesses, and respective clients. However, collecting hyperlocal air quality data can be challenging for several reasons.
For one, the data can be expensive to gather and maintain. For an organization to grant access to hyperlocal air quality data, it needs to have a very big and dense network of data sources/devices. Although governments track air quality data in cities, their networks are not dense enough to pinpoint air pollution hotspots.
This is why PlanetWatch collaborates with citizens to create air quality monitoring networks complementary to government measurement stations. Through this scientific, sustainable, and community-driven approach, PlanetWatch identifies and disseminates the information collected by the devices to build a better world hyper locally and globally while also raising awareness about air pollution issues.
Through PlanetWatch’s network, data is collected every five minutes by monitoring devices that are low-cost – in comparison to the ones deployed by governments – but that meet the highest technological standards on the market today.
Capillary networks are built throughout the territory via these devices – that measure particulate matter, PM2.5, and certain gases, such as NO2, O3, and CO. The accuracy of the devices deployed by PlanetWatch is corroborated through comparisons with government monitoring stations.
The result of this approach is a network with a high space-time granularity that makes it possible to extract detailed information useful for studying the dynamics of atmospheric pollution and, in particular, to analyze in detail the correlations in space and time between the values measured and potentially relevant phenomena such as vehicle traffic, heating plants, and industrial activities, but also to discover hyperlocal events that are generally not detected by the usual monitoring networks.
PlanetWatch’s network collects data continuously over time and – due to its density and hyperlocal approach to air quality – is able to detect even very specific events. The following section details some of them.
A PlanetWatcher observed an abnormal fire from the balcony of his house – where an Airqino device was installed. He immediately recorded a video, so that he could memorize the exact day and time.
He then observed the PM2.5 and PM10 dust values measured by the monitoring device. The charts below illustrate the fine dust values measured by the device (blue lines), compared with the values measured by the monitoring network of a competitor (red lines).
The result is clear: the device detected a peak in the dust at the time of the event, which reached values up to 10 times higher than the average values measured under normal conditions. On the other hand, although the smoke is visible from afar and the risks to the health of the surrounding population are undeniable, the competitor’s network was unable to detect the event.
In the chart below, you can see the measurements of both PlanetWatch sensors (blue line) and reference governmental stations (dashed red line in the figure) in Madrid.
Not only is it visible that PlanetWatch’s devices’ measurements reproduce the profiles of the reference stations, but they are also able to detect hyperlocal phenomena – visible in the blue lines that are not followed by any dashed red lines.
In the following figure, the blue band indicates the ranges of average daily values measured by PlanetWatch’s devices, which are perfectly aligned with the values of the reference station taken as a comparison (dashed red line). The PW AIRQ_430 device (shown in the figure below) measured very significant peaks, which have values up to 20 times higher than the average values measured by the reference stations, representing hyperlocal pollution phenomena.
The following figure shows how PW devices are able to detect hyperlocal phenomena better than competitors (dashed light blue line).
The following figure shows the details of the average daily trends in Paiano, Vietri, Amalfi, Ravello, Maiori, Minori, and Positano (cities in Italy’s Amalfi Coast) during the first three months of 2022.
It is visible that, most of the time, the PM2.5 values remain well below the limit threshold defined by European regulations (25 μg/m3), with the exception of the Maiori and Positano devices, for which exceedances were recorded in the first half of January.
It is interesting to note the pollution peak on 25 March, measured by all the devices.
In order to investigate the origin of this pollution peak, the team analyzed all device measurements on 25 and 26 March. In this regard, see the following figure, where very high peaks of fine particulate are evident, measured mainly in the municipality of Praiano between 8 PM and 12 AM on 25 March and between 2 AM and 6 AM on 26 March.
A Google search revealed that these were fireworks made at a local patron saint’s festival.
Comparing the average dust trend measured by PlanetWatch’s device (blue line) with that measured by the nearest (22 km away) government reference station (red dashed line) shows the accuracy of PlanetWatch device’s measurement, which is able to detect the correct magnitude of the phenomena.
PlanetWatch is reinventing air quality monitoring, replacing unreliable traditional networks with cutting-edge technology and unprecedented scalability.
If you would like to know more, book a free demo of our air quality data API through the form below.
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