We put a PACMAN on someone's home but we weren't ready for what happened next ...

Actually we were ... we got lots of data and that's what we wanted (sorry for the clickbait title ... a scientist has to have some fun right? )

Now in all seriousness, we were very pleased with the data from the first two weeks of PACMAN deployment in Rangiora. They allow us to test the units in a real world setup outside of the researchers' control and evaluate whether the data we get from them can tell us something useful about the exposure of the people inside to particulate matter.

Let's look at data from one unit PACMAN_17 and what it can tell us about the home it was living it.

Temperature

The PACMAN has an internal temperature sensor within its real time clock to keep it accurate. This is not quite room temperature but it approximates it pretty well. See a comparison below between the temperature closest to the wood burner stack (BRANZ logger) and the internal PACMAN temperature. Not bad right!

However, the same issue that I mentioned before remains ... it is not easy to reliably determine whether the heater is on or off from these data but at least we can now see that the temperature signal from PACMAN can be close enough to what we would measure next to the stack ... depending on the specific location of the device

Activity

One of the not quite air quality sensors that PACMAN includes is a PIR motion detector that aims at telling us how active were people around it. We can use this sensor to estimate periods of time where the home is unoccupied. The plot below shows the average of activity per hour of the day which indicates that the home was normally occupied during the day with a lot of running around at midday and after 16:00 and no activity around 05:00 ... so, in all a relatively normal behaviour.

Dust

The main purpose of PACMAN is to track the concentration of particulate matter indoors so we were very keen to see what that looked like in a real world home. As with all low cost sensors, there are several steps between the raw data and something not entirely unlike dust (if you want to know what we do to the data from these dust sensors see here). Below you can see a time series of the hourly Dust.corr concentrations reported by PACMAN and the $PM_{10}.FDMS$ concentrations measured by ECan at Rangiora (note that ECan's data has not been quality assured and it is liable to change in the future).

There are several interesting features in these time series but for the purposes of explaining people's exposure indoors we can see that, except for a couple of events, all indoor peaks in concentration occur around the time outdoor peaks occur which suggests that the indoor dust is coming primarily from outside the home.

Summary

So what does this mean?

It means that PACMAN_17 performed very well and it is able to inform our estimates of woodburner use, house occupancy and the controlling sources for the particulate matter concentrations indoors.

In a word ... RESULT!