Back at the end of July, two South Coast Science Praxis monitors picked up some unusual data. The monitors are installed at Preston Circus, Brighton and the data dashboard for each shows a diffuse and slowly shifting plume of particulate matter (PM1) in the evening on 20th and morning of 21st July.
It wasn’t until one of the team put this together with a distinct smell of damp wood smoke in Brighton that evening, as well as the wildfires in France and Spain, that they considered what had caused these unusual spikes in the PM1 data.
Air Quality Monitoring meets the Real World: Attribution
Monitoring in the lab is easy because it’s a closed system and you can control the conditions. When monitoring air quality (or any other kind of environmental monitoring) in the field, you can expect to find anomalies in your data and this is where it gets interesting.
The question is, what caused those readings and what does it mean for your project? Security camera footage that’s correlated with the air quality monitoring data may help provide answers. In this case, observational data (smell of the wood smoke) and satellite data from the Met Office provided confirmation.
Attribution is often a concern for commercial projects: the stronger the evidence showing where unwanted or unexpected emissions originated, the better the foundation for making decisions about what to do. With a precision air quality monitor, some environmental science and some detective work, it’s usually possible to figure out what happened where, with a degree of certainty.
Small and Near or Large and Far Away?
It isn’t standard practice to use urban areas, like Brighton, to monitor air pollution plumes from distant sources. Ideally, you would select a site with low background pollution levels. However, the quality of data provided by Praxis monitors makes it possible to distinguish between local and distant sources of air pollution.
Sharp spikes indicate a nearby emissions source
With a monitor by a busy road, like our installation at Preston Circus, emissions from individual cars in slow traffic show up as sharp spikes on the data dashboard where emission levels rise, peak and decline over a period as short as 30 seconds. These can be easily identified in the data output from a Praxis monitor because it uses a sampling rate of 10 seconds, individually capturing these short-lived, highly local changes in air quality.
In the image below you can see an example of emissions from a single vehicle at 1:55am on 21st July, or log into the demo dashboard for the Urban or the Cube to see for yourself.
NB username: firstname.lastname@example.org and password Science123
Gentle curves indicate a distant emissions source
The plume that showed up in the data from 20th and 21st July was very different. The data dashboard shows a gentle curve starting at approximately 18:00 and the increase in pollutant levels takes place over many hours. This is consistent with particulate matter carried and dispersed by the wind over a large distance. Essentially, it’s possible to measure the distance from monitor to pollution source by the rate of change in pollutant levels (to a certain level of assurance).
We contacted the Met Office for verification. Using satellite and observational data, they confirmed that wood smoke from the wildfires had travelled to the South of England with an incoming weather front. The particulate matter picked up by our monitor had travelled over 400 miles from the Gironde to Brighton.
Device design, independent certification and data quality
At South Coast Science, we design and manufacture air quality monitors that provide data for compliance, reporting and decision making for our government, industry and utilities customers.
If you’d like to find out more about how our monitors can support your air quality monitoring projects please visit our Products page or contact our Sales Director, David Johnson.
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