This summer, I undertook a small research project that examined institutional policies related to climate change. These mostly included Climate Action Plans and Sustainability Plans, as well as reports, updates, and any other relevant documents available on institutional sustainability websites.
My focus was on how these policies discussed Scope 3 emissions related to flying (usually termed “business air travel”). I wanted to see how these policies discussed and addressed the issue of flying in academia.
**Note: this is now a [package](https://github.com/acircleda/footprint)!**
I am hoping to soon be working with a data set of travel data for which I will need to calculate carbon emissions of flights. There are a number of online calculators, but none that I know of that could be pulled into R to call as a function and or be used to process data.
I recently started using TAGS to start archiving Twitter posts with key search phrases for later exploration and possible research. One of my search phrases was the hashtag #flyingless. #flyingless typically is appended to posts related to reducing the carbon footprint associated with flying, often flying to and from conferences, but also flying in general.
By just scraping the past few days worth of data, I found a few interesting takeaways.
Google collects a lot of data on us. If you have Google Maps, chances are your location is being tracked, too. Unless, of course, you have it disabled. But, if you don’t, you’d be surprised by the amount of location data (and its accuracy) contained in your Google Timeline. Many worry about Google’s tracking, but for those of us who don’t, there is some potential fun we can have with our own data.