ROCIS Data Explorer - Participant Example 4

This link will take you to the Data Explorer site: https://bluetree.shinyapps.io/lcmpexplorer2/

In the case below, we are discussing Example 4, which can also be accessed by entering the participant code m6i6.

Example 4 on the LCMP Data Explorer is easy to understand. In Example 4, we are dealing with a house in summer where windows are generally wide open. Many ROCIS participants have their windows wide open in summer to aid in cooling and/or general ventilation.

That means that the indoor air and its particles are almost identical to the outdoor air. When Pittsburgh air is dirty and full of particles, so is the house.

Here is Dygraph of the 3-4 weeks of monitoring:

Particle count graph from June 4 to June 28

You can see clearly how the Dylos small particle trends mimic each other. Here is an period where the three monitors (outdoor, indoor, and roamer) are near identical, first as a graph with an exponential scale and then using a linear scale.

Particle graph count with exponential scale

Particle graph count with linear scale

On the other hand, it looks like there were a couple of days, June 14-17, where windows were closed and the particle counts started deviating. That is good because outside particles were getting high and ugly overnight during that period.

Particle count graph June 14 to June 17

In winter monitoring, we see some of our participants have indoor particle counts that are 10-20 times lower than outside, largely due to the way the house structure and envelope provide an effective filter. Example 4 shows the opposite effect—the house envelope provides no protection as windows are wide open.

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