CONA - Community Observation Networks for Air

In air quality lingo  we normally refer to small areas of increased pollutant concentrations as hot spots  but since this story is about the temperature  field I needed to use something else ... warm spots  will do. As part of the measurement campaign we deployed in Rangiora we not only used ODINs but also four weather stations (like the one on the picture) scattered around the town to explore small scale wind flows and how uniform or otherwise the temperature field is in the area. Before we dive too deep in the analysis, let's pause and look at the two kind of temperature sensors used here. First is the meteorological sites that have thoroughly calibrated and well housed thermometers, protected from the sunshine while the ODIN thermometers were ... well ... not perfectly housed (see image of the inside of an ODIN) and then put in plain sunlight attached to lamp posts (see image of ODIN attached to a lamp post). Now, don't despair! There is a reason why the ODIN tem...

The main reason we asked for some volunteers to accept temperature sensors in the home was to track when people were using their woodburners and how that might change from day to day. But the data from these sensors reveal a whole lot more information if you care to look and we’re just starting to look now. The sensors themselves were thermocouples provided on loan by BRANZ  the building research institute. They consist of a probe which was attached to the top of the firebox and a logger placed nearby. So far I have looked through data from 9 of the 14 homes we surveyed. In a moment, a taste of some of the things we can work out from the indoor temperature data. But first, a quick look at the outdoor temperatures. Below is a 'box plot'. All of the data from every days is combined and sorted into hours. The middle 50 % of all data lies within the box (the short horizontal line is the average). The top and bottom 25% are represented by the dashed lines. This chart shows that, o...

If you thought that we've gone away ... you're partly right, we've been away  but not in a bad way! About a week ago we got our first full set of data from a few of the participants in Rangiora and just to give you an idea ... for every home  we have about one million records with between 5 and 10 parameters each ... that's a lot of numbers! So, yes, we've been away but it has been trying to get our heads around this large dataset ... with various levels of success... as a German general said in the 1800s:  "No plan survives contact with the enemy" . At the beginning of this campaign we thought that the temperature data obtained through the iButtons  and BRANZ's loggers was going to be simple to interpret. High temperature = heater on, low temperature = heater off. The next level in complexity would be ECan's temperature and $PM_{10}$ data as it is standard compliant and we have a long time series for that location that would give us some context ...