By Colleen Marciel F. Rosales, Ph.D., Strategic Partnerships Director at OpenAQ
This March I visited Ghana, Rwanda and Kenya for a three-week air pollution and open data outreach adventure, as well as to attend the CAMS-Net & AfriqAir General Meeting. I also got to try out fufu, visit the Kigali Genocide Memorial, and see a lion up close!
Let me take you back in time to travel with me and the handy little personal exposure device I carried with me called the Atmotube.
I brought the Atmotube with me almost everywhere I went. It was actually easy to forget that I had it since it’s so lightweight and tiny.
The Atmotube partners with an app (available on both Apple and Android). I’m using an Android phone, and this is what the app looks like:
The app shows both its internally calculated “Air Quality Score,” as well as an Air Quality Index (AQI) based on the reference index you choose (I chose the US Environmental Protection Agency’s as mine). It’s also important to note that these two scales are somewhat opposite: the air quality score (number) is higher when there are less pollutants and therefore the air quality is better. On the other hand, for the AQI, the number is higher when the air pollutant concentrations are higher (i.e., when the air is worse).
The app also shows you where the current temperature and humidity lies on the “comfort zone” and has a note below this grid that says, “Generally, people feel comfortable at temperatures between 71.6 °F to 80.6 °F and at a relative humidity between 40 to 60%.” I have a smaller range of comfort than that, but of course everyone has a different level of comfort depending on what they are used to where they live. The app also aims to educate and includes articles with recommendations on how to avoid air pollution exposure.
Another neat visualization on the app is the air quality map, which shows data from all Atmotubes all over the world. This is a little tricky to parse out since the context of each measurement is different from one data point to another. Nevertheless, it’s cool to see the distribution of Atmotube users all over the world.
For real time alerts and a quick look on the data, the app is quite easy to navigate. But naturally, as an air pollution scientist, I also wanted to analyze the data myself. I didn’t find time to do this till two months after my trip, so I wondered if my data would still be available. Luckily, it was. I was able to download a .csv file and look at it using Wolfram Mathematica. Each .csv file includes the following parameters: Date, VOC (ppm), AQS, Air quality index (AQI) — US, Temperature (°F), Humidity (%), Pressure (mbar), PM1, (ug/m3), PM2.5 (ug/m3), PM2.5 (avg 24h, ug/m3), PM10 (ug/m3), PM10 (avg 24h, ug/m3), Latitude, Longitude.
My interest was in the smaller particles as well as VOC, so I plotted those out in a time series.
I didn’t keep a log of what I was doing at each exact minute, and while there are latitude and longitude data, it’s a bit tricky to tease out which ones would be indoor and outdoor concentrations, especially since I was in a tropical area where the indoor and outdoor temperature would typically be similar. Nevertheless, I think it’s safe to say that the extremely high VOC readings are during times when I sprayed personal care products like perfume or hand sanitizer. (I noticed my ATMO phone app will alert me that “Air is severely polluted” — complete with a bright red notification — and the air quality score would be zero when I sprayed any VOC-laden product in my small unventilated hotel room in Nairobi — which of course, makes sense.)
Being able to download the .csv file also allowed me to create statistical plots, such as histograms and five-number summaries. There’s also a wealth of other data that I can explore.
Now that I am back home, I hang my Atmotube in the common area. It has been quite interesting to see the air quality score go to zero whenever I cook (and how it remains low for hours… now I can estimate my air exchange rate).
Overall, I think the Atmotube is a neat air quality sensor that brings air quality awareness and is a great tool for air quality data literacy. It also makes you think more about what environmental factors might be contributing to your exposure to invisible air pollutants in your daily activities.
Correction (August 15, 2023): Instances of the usage of the term “mountain lion” are now corrected to “lion”.