Air Quality Citizen Science project – early testing of the PM sensors

Following on from previous posts describing the PM sensors that we are using, the next steps are about testing them before giving them out to volunteers.

This post will describe some of these tests and also give some insight into what data is generated and how it can be used.

Some simple trips with the sensors allow me to capture data and make sure they are working as expected. The data that is captured is stored on the phone (android smartphone) and can be later uploaded to the aircasting website or to any other source. The aircasting website is a community mapping development by HabitatMap and provides a form of crowd-sourced data. An example of this is shown below and can be found hereaircasting_map

Beyond this pooling of data in a community map like the aircasting website, it’s also possible to look at individual data streams. This was part of the testing process for our AirBeam sensors. The data from one trip with one of the sensors (unit 1 for reference) is shown in the diagram below:


This shows a single trip in south Liverpool near Allerton Road. The individual data points are visible, with a simple colour coding according to the spread of the data i.e. green are lower values and red are higher values: this does not necessarily mean that red is unhealthy however, it’s just a higher reading.

The diagram below shows the same trip and data but zoomed it for one part. The reading for one data point is also shown. This reading was taken on 13 October 2016 and the PM reading was 13.12 micrograms per cubic meter.


At this stage I will not go further into how this data can be used. The purpose of this post is simply to share some insight into the testing process. A goal of the project is to find out how this data can be useful to individuals and community groups – at this stage we just want to make sure the data is being generated and that it looks in line with expectations. The journey above supports the view that this sensor is working as expected.

More to follow on testing.

Air Quality sensors: first steps to set them up

A previous post announced the arrival of our first two #airquality sensors. These two sensors measure particulate matter (PM); we are still waiting on delivery of two more sensors, which will measure nitrogen dioxide.

Now we’ve got these sensors, the first steps in our project plan are about setting them up before they are ready for use by volunteer participants. We also need to do some proper testing, but more on that in another post.

Below is a picture of our two AirBeams to measure PM:


For the technically-minded the AirBeam is based upon the Arduino Leonardo. In addition to the particulate matter sensor inside the case, there is also a sensor to measure temperature and relative humidity. The AirBeams are battery powered and charged using a USB cable. These AirBeam needs to be used with an Android smartphone and a specific “app” has been developed for their use – the “aircasting” app is found here.

The AirBeam connects to the Android smartphone using bluetooth technology. The Android smartphone is primarily needed to provide a GPS location for the data that is recorded by the sensors. Additionally the microphone of the phone can be used to record local noise levels – potentially providing some insights into local noise pollution levels, although this is not the immediate focus of our project.

The screenshot below shows the aircasting app and the readings from the sensor. So, at this point in time (readings are taken every few seconds) PM was 6 micrograms (one millionth of a gram) per cubic meter. At the same time, relative humidity was 51%, temperature 60F and the sound level was 81dB. The colour coding can be configured and is designed to give a quick idea about current levels.


These readings update continuously and can be recorded on the smartphone for mapping or analysis. More on this in a later post.

Michael has been using this AirBeam for the last year or two and so is very familiar with its use. They are great devices, but of course have their limitations. One limitation is the need for an Android smartphone and so volunteers will need to have an appropriate phone for the sensor to work. This is a constraint, but we feel we can still learn a lot during the project.

More information to follow on the progress of our tests with these sensors and how the data can be used.

The first sensors arrive – unpacking the AirBeam PM Sensors

For our Air Quality project we have ordered:

The PM sensors are called AirBeams and were ordered from Habitat Map in the USA.

We ordered them 31 August 2016 and we’re glad to say they arrived a few weeks later. There were some minor customs charges, but at least we were underway!


Opening up the box and there are two lovely new AirBeams. which we promptly labelled with a Sharpie pen – Liverpool FoE Sensor #1 and Sensor #2 are here!


Next steps are to start testing and configuring these sensors in preparation for giving them to volunteers. We are still waiting on the NO2 sensors as well.


Air Quality in Liverpool


We are looking at air quality within Liverpool as part of our local efforts.

We are currently running a “citizen science” project. To do this we are grateful for funding from the Liverpool Clinical Commissioning Group.

This is a small-scale project with some simple objectives:

  1. We want to understand more about the different technologies that can be used to support citizen science initiatives around air quality
  2. We want to understand how these technologies, and the data they generate, can be used to help individuals and community groups.

No doubt there will be other learning along the way. For example, we are interested in how this sort of community-level engagement and “hyperlocal” data gathering can be used to supplement and complement city-level and national air quality monitoring and management.