Are Low-Cost Sensors Reliable for Smoke Monitoring?

An increasing number of air quality data providers are making use of low-cost air pollution sensors for monitoring smoke travel during wildfire events.

These sensors are available for purchase by individuals and are becoming more and more popular. But are they reliable for smoke monitoring during these extreme events?

The Importance of Accurate Particulate Matter (PM) Reporting For Smoke Monitoring

PM is the main type of pollution caused by wildfire smoke – short-term exposure isn’t healthy for anyone but vulnerable groups are at particular risk from smoke inhalation.  As such, it’s extremely important to monitor the changing levels of this type of pollution during these extreme events.

fire and smoke monitoring from a distance

Some Low-Cost Sensors Require a Tricky Conversion Process

During a wildfire, air quality data providers use AQIs (Air Quality Index) to communicate air pollution levels. AQIs are based on measuring air pollutant levels by mass (i.e. how many micrograms of Particulate Matter there are per cubic meter of air). This is the method used by governmental smoke monitoring stations. 

Many low-cost sensors, however, measure Particulate Matter in an optical way (i.e. they monitor how the particles interact with light) – which is different from this more common method of measuring PM by mass. As a result, the data produced by low-cost sensors needs to be converted into mass

Importantly, different types of particles are heavier or lighter than others, on average. A dust particle, for example, is heavier than a particle you would find in wildfire smoke. This means different types of Particulate Matter need to be converted in their own unique way for the resulting information to be reliable. 

Bottom line: If the conversion process doesn’t take the different types of particle into account, the translated information probably won’t represent an accurate picture of air quality.

Damp Air & No Drying System

When the Relative Humidity in a particular area is particularly high (we’re talking 80% and up), this can interfere with the monitoring of particles. To avoid such interference, a drying system should be used at the inlet of the sensors, but low-cost PM sensors usually don’t include this kind of drying system.

Are the Sensors Being Maintained?

Low-cost sensors are typically calibrated before they get shipped to their users. However, their reliability can degrade over time e.g. because of temperature variations outdoors and clogging from plant debris, insects and more.

To ensure ongoing reliability, it’s important that the sensors are checked and maintained on a regular basis. This is down to the individual owners – it’s their responsibility to assess if their sensor is functioning as it should be, and that it is kept clean. 

Of course, it’s pretty difficult to confirm whether or not this actually happens in the majority of cases.

Location Matters!

The specific locations of different low-cost sensors could result in skewed readings.

If one person places their sensor next to a BBQ and another in an enclosed garden, their readings are naturally going to be very different, even though the true picture of ambient air quality might be very similar.

Not Enough Sensors?

When it comes to crowd-sourcing air quality information from low-cost sensors, the question of number becomes extremely important.  Air quality is extremely dynamic and changes from street to street – this reality is even more dramatic during a wildfire. This means there needs to be a lot of sensors in an area to provide an accurate representation of fast-moving smoke pollution. 


In Conclusion

Low-cost air quality sensors can be extremely useful for monitoring specific pollutant levels. However, without the ability to conduct in-depth analysis or advanced QA around their reporting, there are some question marks around their reliability.

During extreme events like wildfires, it’s important to be able to locate safe spaces with clean air. The unfortunate reality is that real-time air and smoke quality monitoring during these extreme events can be extremely challenging to represent accurately in real-time. We’re seeing this time and time again in the live information reported by government smoke monitoring stations and low-cost sensor providers. 

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Dr Yvonne Boose

Data and Accuracy Lead Scientist @BreezoMeter. I hold a PhD in Atmospheric Physics and formerly worked as a Postdoc at the German Aerospace Center. I love translating science to real-life improvements at BreezoMeter.