A previous post has reported that we have recently received the 2 Air Quality Eggs that are part of the Liverpool Friends of the Earth Citizen Science Air Quality Project. I have used these Eggs before, but there are some new features with these devices, which are important for this project – specifically they offer:
- GPS for location tracking and so we can go mobile with them; and
- an onboard SD card for local data storage to complement the mobile data capture
After the unpacking the first stage in the project process is to test them and make sure they are going to be fit for purpose for our volunteers.
The initial set up connects to my WiFi and data is reported to openSensors. Without too many hiccups the Egg is reporting data. The validation of this is not pretty, but is a format like the screengrab below, which shows the Egg reporting Carbon Monoxide, Nitrogen Dioxide, Temperature and Humidity (just off-screen):
Once data is flowing it’s then useful to do some sense-checking on the data and also check the new features i.e. GPS and the onboard storage. So I took the Egg on a trip into Liverpool. During the journey, the Egg is powered by a battery and stores data on the SD card. This data was then later downloaded for analysis.
The picture below shows this data imported into QGIS – an open source GIS package – for analysis.
The GPS appears to be working fine. This was indeed the route taken, using a mix of bus and walking. You can see the larger spacing of the readings when the bus is moving at speed.
The colour coding used is just a spread of the data. Work to be done later is to determine the appropriate colour coding according to national guidance from health agencies and other expert bodies. For now, the colour coding simply shows the spread of data – with dark red being the highest values and white the lowest. The legend in the top right shows the schema and the associated numbers in parts per billion (ppb) of NO2. These figures should not be used in isolation. There’s always the possibility that an individual sensor is faulty or there is some other issue. Confidence comes with increased numbers of sensors and consistent readings over time.
One of the challenges that the test revealed is more about the physical side of the egg than the electronic and information side. We’re going to have to think about how someone can carry the egg, because it’s more bulky than the AirBeam PM sensor. We also need to make it a bit more weather proof and probably buy 2 portable batteries for our 2 sensors when they go mobile.
First tests are looking good though. Next is to get the other Egg up and running, do similar tests with it and then also do some comparison tests to see if these two eggs report similar data. I can compare these two to my other Air Quality Eggs that I’ve got from previous work over the last few years. More on this later.